1,823 figures from 148 papers

Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the tissue domains and the cell-type distributions?
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Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can 3D spatial transcriptomics reveal spatially variable genes whose expression patterns are only apparent when multiple tissue sections are analyzed together in three dimensions?
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Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes most specifically mark each spatial tissue domain, and how prevalent and highly expressed are they within their domain?
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Yan Y. and Luo X. - 2025

BACT: nonparametric Bayesian cell typing for single-cell spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the transcripts located in tissue?
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Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do deconvolved cell type proportions match known anatomical region boundaries in the mouse brain, and are their top marker genes spatially consistent with those regions?
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Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does expression of a gene differ across patient categories?
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Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Does spatial proximity to tumor cells influence the functional state of immune cells?
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Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : Physical
What is the raw visual evidence for the subcellular localization of the module genes within individual cells?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of disease subtypes?What is the tissue morphology and architecture?
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Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types engage in long-range secreted signaling with a given cell population?
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Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell types spatially enriched in the tissue, and does it match known anatomical layers
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Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How are spatial domains distributed in embedding space with 2D analysis?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Sequencing-basedModality : SimulatedVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What is the spatial distribution of the estimated latent expression effect of a specific protein across the tissue network?
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Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do cells of a specific type show higher gene expression in regions of high pathological burden?
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Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue is a specific transcriptional program spatially active?
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Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What genes are expressed in cells based on their neighboring cell types?
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Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Radial network plotChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where in tissue space do predicted ligand-receptor interactions occur between specific cell types?
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Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does cell differentiation state, as captured by pseudotime, map onto the physical spatial organization of the tissue?
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Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : ScatterplotComparative Design : JuxtapositionScalability Strategy : No scalability strategy (Item-level)
Do interaction-context-dependent genes show systematically higher directional association scores compared to the rest of the transcriptome?
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Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do different methods identify spatial domains?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
How are specific cell types spatially distributed across tumor tissue sections?
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Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What genes are differentially expressed across spatial neighborhoods?
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Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
What cells are in the spatial neighborhood of a specific cell?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Can patients be grouped into distinct subtypes based on the composition of their spatial tissue niches?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesScalability Strategy : Summay/Aggregate
Which cell types participate in different stages of a communication relay?
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Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are specific cell types distributed?
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Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Modality : GenomicsOther : UI / Screenshot
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Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are major cell classes spatially organized in tissue?
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Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the frecuency of specific cell clusters vary along a spatially defined anatomical gradient?
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Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show the highest spatial variability across a tissue section, and where are they expressed?
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Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue domains spatially distributed across a tissue section?
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Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do driver genes change spatially and temporally during lineage development?
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Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns for a selected gene?
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does marker gene expression validate cell type assignment across the organism?
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Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the spatial domains?
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Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How does the activity of specific biological pathways vary across spatially defined regions within a tissue?
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Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do IC weight compositions vary across prostate cancer spot clusters in UMAP space?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Radial network plotChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where in tissue space do predicted ligand-receptor interactions occur between specific cell types?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific proteins expressed in both expression space and physical tissue space?
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Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the cellular composition of a tissue vary across spatially defined domains?
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Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Simplex-based scatter plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do features shift between conditions?
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Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What cancer subpopulation trajectories emerge from pseudotime inference in breast cancer tissue?
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
do their top marker genes match known layer-specific genes?
View paper
Li et al., 2023

Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : PseudotimeMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
How is the trajectory inference of the cells?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially organized within the hypothalamus?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
Do different cell types vary in the distribution of their contribution scores to spatial cell type classification?
View paper
Larsson L. et al. - 2023

Semla: a versatile toolkit for spatially resolved transcriptomics analysis and visualization

Data Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : HexplotChart Type : Line ChartCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does gene expression change with spatial distance from a defined region of interest?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
what are the diferentially expressed genes in each spatial domain?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are tumor regions located within the spatial architecture of a tissue section?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell types ?
View paper
Hägele et al., 2024

Visual Compositional Data Analytics for Spatial Transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spots sharing a similar cell type proportion profile (as grouped in embedding space) correspond to spatially contiguous or organized regions on the tissue?Do spots with distinct cell type proportion patterns cluster into spatially coherent tissue regions?Which k-means cluster groupings of cell type proportion patterns are present and selectable for comparison?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial density distribution of a chondrocyte marker gene?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue is a specific transcription factor regulon active, and what biological processes does it regulate?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial tissue architecture is present in a diseased tissue sample?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pixel MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are specific cell types spatially located across treatment conditions?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the average cellular composition of each spatially defined tissue domain?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How many spatially coherent domains can be identified at single-cell resolution in brain tissue?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureBiological : TissueAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : N/AData Components : StatisticMetadata : No metadataModality : Sequencing-basedVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/Filtering
How strongly does gene expression correlate with developmental ancestry?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a specific marker in tissue as measured by immunofluorescence?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Does a disease condition reduce the spatial purity of a specificcell-type domain?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionAbstraction : PartialChart Type : Dot ChartChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial localization and expression correlation between markers in both healthy and diseased tissues?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial organization of major hypothalamic nuclei in a reference brain section?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of individual genes across a tissue section, and where do these genes map within the overall gene expression landscape?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : Radial PlotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : CircularScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Is the difference in radial transcript spread between module and non-module genes specific to the diseased state?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What gene expression signatures characterize each transcriptomically defined cluster?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
which spatial domains exist in this tissue section?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
What is the three-dimensional organization of transcriptionally defined spatial domains across stacked tissue sections?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do observations cluster based on molecular similarity?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue regions distributed across a tumor section?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of cell type-specific genes?What are the spatial expression patterns of specific genes across tumor regions?What is the spatial distribution of cell types in tissue?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types distributed across a tissue section?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the global spatial distribution of cell types across a tissue section as predicted by a deconvolution method?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the body is a gene most strongly expressed, and does its spatial pattern align with known anatomical structures?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What cellular structures and compartments are associated with genes whose expression depends on interactions between specific cell types?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the cell clusters present in the tissue?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
Which cell types are present?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are pathologist-defined tissue regions distributed across a cancer tissue section?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial communities?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a continuous spatial coordinate vary across a tissue section?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is the composition of mixed cell populations distributed across tissue space when single-cell resolution is not available?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which genes show spatial co-expression patterns within tissue domains?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched among the spatially variable genes identified by a given method?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tumor subclones spatially distributed within a tissue section?
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Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do genes identified as layer-specific show spatially restricted expression patterns that align with the annotated cortical layers?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What biological processes are enriched among genes that vary along a spatial tissue gradient?
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What cell types are present in a fraction of tissue?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does a cellular morphological feature change across time or spatial location as a proxy for a functional state?
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Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : TimeMetadata : No metadataModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
How does gene expression correlate with developmental ancestor probability?
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Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does cell abundance differ between tissue regions and treatment conditions?
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Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do genes associated with specific cell types show spatially localized expression patterns consistent with the known distribution of those cell types?
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Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological organization of a tissue section?
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial domains exist in this tissue section?
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Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does a coordinated gene expression pattern evolve across discrete developmental time points?
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Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where do distinct cell populations localize in a tumor and what genes mark each domain?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
What is the three-dimensional spatial distribution of a specific tissue type (CNS) in a whole-embryo reconstruction?
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Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do hippocampal cells from different anatomical subregions form distinct transcriptional clusters, and can these clusters be labeled by predicted spatial origin?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
Do individual genes show spatially coherent expression patterns consistent with known biology?
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Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology?
View paper
Shi M. et al. - 2024

STPDA: Leveraging spatial-temporal patterns for downstream analysis in spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How does the expression patern of interacting ligand-receptor gene pairs look?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the computational method identify cancer tissue heterogeneity?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the estimated spatial expression of a specific gene change across different disease time points?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cells organized into anatomical layers within the tissue?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression patternes of gene expression?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : Disease stateMetadata : No metadataModality : Sequencing-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial organization and cellular composition revealed by immunofluorescence?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pixel MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How does gene expression differ between predicted cell types and background?Where are specific cell types spatially located in tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do spot clusters spatially organize across a prostate cancer tissue section?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Where are the genes being expressed?Which cell types are present?
View paper
Kamel M. et al. - 2024

SpatialOne: end-to-end analysis of visium data at scale

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : No comparative designComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct cell types spatially distributed across a tumor tissue section?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
Which cancer-related pathways are enriched in different tumor regions?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the anatomical structure of the tissue?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularAbstraction : CompleteChart Type : spectral plotsCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What does the immediate spatial neighborhood look like around two cells belonging to distinct subclasses?
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Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatially resolved expression patterns of cell-type-specific marker genes vary across a tissue section?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a marker gene within a tissue section?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotChart Type : Line ChartCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What biological pathways are enriched when selecting cells based on high importance scores for a set of receptor genes?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in tissue space does significant ligand-receptor co-expression occur, and can spatial binning enable this analysis at scale?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How are spatial domains distributed in embedding space with 2D analysis?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : No comparative designScalability Strategy : Summay/Aggregate
What are the characteristic cell-cell interaction patterns within a spatial community?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial expression gradients relative to tumor boundaries?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct cell types spatially distributed across a tissue section as predicted by probabilistic cell type assignment?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Dot ChartChart Type : HeatmapChart Type : Line ChartChart Type : Motif Logo PlotChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does gene expression vary across different cell populations?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Network graphChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are cell-cell communication interactions spatially localized?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How predictive is the neighborhood cell composition for determining the central cell's identity across all detected cell types?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How the relationships change between disease state?What are the relationships between the pairs of different cell clusters in healthy and diseased tissues?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial density distribution of a chondrocyte marker gene?
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Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the known anatomical laminar structure of the tissue region being analyzed computationally?
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Fernández-Navarro J. et al. - 2019

ST viewer: A tool for analysis and visualization of spatial transcriptomics datasets

Other : UI / Screenshot
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Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the cells located in the tissue?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Network graphChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are the strongest cell-cell communication interactions spatially localized?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent cell communities exist within the tumor microenvironment?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?
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Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What disease associations characterize molecular spatial domains?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
What is the three-dimensional spatial distribution of a specific neuronal subtype across stacked tissue sections?
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Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does the size of a cell's transcriptomically similar spatial neighborhood reflect its layer identity and position within the tissue architecture?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are subtypes of a specific cell lineage spatially distributed within the tissue?
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Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological organization of a tissue section?
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Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the major anatomical regions in a given brain area according to a reference atlas?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are distinct hippocampal neuron subtypes spatially distributed across multiple tissue sections?
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Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial relationships between expression programs?
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Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can ultra-high spatial resolution transcriptomics reveal the fine-grained spatial organization of cell types ?
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Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What distinct cell populations are present in the dataset, and how are they distributed in different time points?
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Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : Force-directedScalability Strategy : Summay/Aggregate
How do molecular spatial domains relate across multiple samples and disease states?
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Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a known anatomical reference map define the spatial boundaries of brain regions?
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Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do known cancer marker genes show spatially localized expression in tumor tissue?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How frequently do specific pairs of cellular neighborhoods form edges in the estimated interaction network, indicating likelihood of cell-cell interaction?
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Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains in the tisWhat are the spatial domains in the tissue?
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Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do marker genes show the expected expression gradients across ordered tissue layers?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : No comparative designScalability Strategy : Summay/Aggregate
What are the characteristic cell-cell interaction patterns within a spatial community?
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Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which pairs of genes are spatially colocalized or mutually exclusive across a tissue section?
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Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell type mixture proportions across a tissue section?
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Ye et al., 2023

Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Bar plotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are multiple genes simultaneously distributed across functional zones of a tissue, and do they show mutually exclusive or co-localized spatial patterns?
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Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the organization of the cells?
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Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What is the order of cell states along a developmental trajectory, and how does it map onto a low-dimensional representation of gene expression?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are distinct cell-cell communication networks spatially organized?
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Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Are tumor invasiveness marker genes preferentially expressedin specific spatial tissue domains?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cell type relationships and neighborhood structures evolve across disease time points in a dynamic network representation?
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Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the spatial organization of cortical layers look like under histological staining, and how are they delineated by expert annotation?What is the spatial distribution of tumor and non-tumor regions in a cancer tissue section as defined by expert annotation?
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Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell types across the human intestine Visium section?
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Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do identified spatial domains correspond to marker gene expression patterns?
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Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do unsupervised spatial clusters partition a cancer tissue, and which clusters correspond to cancer-associated regions?
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Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do known layer-specific marker genes show spatiallyrestricted expression matching expected tissue architecture?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cells organized into anatomical structures?
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Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which ligan-receptor pairs show spatially resolved communication between cell types?
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial density distribution of an ossification marker gene?
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Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What do individual fluorescence channels reveal about cell-type distributions?
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Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What spatial clusters are present?
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Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Are there co-ocurring signals?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially organized within a tissue section?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which ligand-receptor pairs are strongly correlated with the specific molecular factors of the central and niche cells?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes show expression changes along a spatial tissue gradient?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the cellular composition vary across spatially defined tissue domains?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological organization of a prostate cancer tissue section?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue morphology and expert-annotated spatial layer structure look like in a given sample?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which communication signals are strongest and shared across samples?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
How are cell-type domains spatially organized across a high-resolution spatial transcriptomics slice?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What major cell types are present in a tissue sample as revealed by single-cell transcriptomics?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
What are the spatial domain clusters in the dataset?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How are molecularly defined subregions distributed across anatomical regions?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do pathway activities vary across spatial domains?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : CategoricalData Components : StatisticModality : Sequencing-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What pathways define a cell cluster?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What marker genes characterize each spatially defined cell population?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific signals localized within spatial structures?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the spatial distribution of a cell lineage change across developmental time?
View paper
Peng W. et al. - 2024

MVCLST: A spatial transcriptome data analysis pipeline for cell type classification based on multi-view comparative learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the raw tissue morphology of the sample?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what are the spatial patterns of variation in the gene expression data?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does local intrinsic dimensionality of gene expression reveal tissue boundaries and structural heterogeneity within a spatial transcriptomics dataset?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells from different cortical layers cluster in transcriptional space, and do layer-defined groups align with known cell type identities?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the molecular spatial domains across multiple tissue samples?
View paper
Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of the SVGs across the dataset?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are the module cells spatially organized within the tissue, and is there visual evidence of intercellular interactions or localized transcript enrichment at cell boundaries?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial communities?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene expressed in a spatial domain?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringOther : UI / Screenshot
Where within cells are specific transcripts localized?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the boundaries between spatially distinct transcriptomic domains within a tissue section?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which biological pathways define the molecular identity ofeach spatial tissue domain?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Modal AlignmentAbstraction : PartialChart Type : Flourescence tissue imageChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do imaging-based and transcript-based cell segmentation methods compare in specific tissue regions?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does gene expression varies across clusters?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : Physical
How do cell type distributions vary across tissue sections?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the manual annotation of the tissue sections?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of marker genes and spatial domains?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do molecular profiles cluster in latent space?What are the molecular spatial domains identified through latent space clustering?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Are spatial gene expression patterns reproducible across different tissue sections?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology and architecture?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial organization emerges from clustering the reconstructed spot-level communication graph?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatial gene expression patterns do contrastive components capture across brain regions?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do spots from different tissue slices integrate into a shared transcriptional space, and do they form a continuous trajectory reflecting tissue layer organization?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteAbstraction : PartialChart Type : Network graphChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/AggregateOther : UI / Screenshot
How can users interactively explore cell-cell communication networks in spatial context?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are distinct tissue domains located within a sample?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Anatomical & Spatial Domain DiscoverySpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of RCC cells across tumor regions?Which genes show region-specific spatial variability?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tumor and non-tumor tissue regions spatially distributed within a cancer biopsy?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
what biological pathways are enriched?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatially resolved independent components identify and delineate distinct tissue substructures?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are layer-specific neuronal populations spatially distributed across cortical tissue?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the similarity structure among meta-programs identified across tumors and technologies?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of the cells?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where are hepatocytes located based on marker gene expression?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across the hypothalamic preoptic region?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Which are the cell types presents in tissue?
View paper
Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the gene expression profiles that characterize the cell sub-populations?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What are the expression patterns of domain marker genes across samples?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : DendogramChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedLayout : Space-fillingScalability Strategy : No scalability strategy (Item-level)
Do spatially variable genes cluster into distinct spatial expression patterns, and where in the tissue are these patterns located?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Modality : scRNA-seq
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are most specifically expressed in each spatial region and can serve as markers for that region?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue is a specific functional gene program active?
View paper
Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
What gene regulatory relationships are inferred for a cancer-associated gene in tumor regions?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are specific cell populations spatially distributed ?
View paper
Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
Does the expression of a gene in a focal cell type differ based on the proportion of a neighboring cell type in its spatial neighborhood?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How many spatially distinct gene expression domains can be identified in a tissue section?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the known anatomical regions in the mouse brain section under study?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which spatial regions and time points contribute moststrongly to each latent pattern of gene expression variation?
View paper
Larsson L. et al. - 2023

Semla: a versatile toolkit for spatially resolved transcriptomics analysis and visualization

Data Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Line ChartCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show similar spatial expression patterns across the tissue?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What cell types are present in the tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the activity of a gene co-expression module vary across cells in both transcriptional and physical tissue space?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What are the pairwise similarities between cells after embedding refinement?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue is a specific transcriptional program spatially active?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What gene signatures characterize different tumor spatial neighborhoods?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What cell types are present in a tissue, and how are they categorized?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does a gene flagged as spatially variable by 2D analysis show a genuine 3D spatial pattern, or is its variability an artifact of 2D slice analysis?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : StatisticModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What is the variability in spatial patterning scores across gene family members?
View paper
Gong C. et al. - 2024

SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do transcriptomically distinct cell populations occupy spatially defined regions within a tissue, reflecting its underlying anatomical architecture?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is chromosomal instability spatially distributed in tissue?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cells from tumor and normal tissue compartments spatially distributed within a combined tissue section?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : Microscopy imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How is a functional module of genes expressed in specific tissue structures?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What cell types are present in a fraction of tissue?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific marker genes expressed, and do their spatial patterns correspond to known anatomical regions?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are different cell states spatially located in 3D tissue?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the distinct spatial expression patterns of gene groups in tumor tissue?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct anatomical layers organized within a brain tissue section?
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Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
What is the spatial distribution of cell-type or region compositions across a tissue section?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types preferentially co-localize in space within a tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are multiple genes distributed across the tissue?
View paper
Long et al., 2024

Deciphering spatial domains from spatial multi-omics with SpatialGlue

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoverySpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures in the tissue?What is the tissue morphology?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
At what spatial distances are specific subcellular compartments preferentially co-localized with each other?
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Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the relative abundance of distinct cell types within each spatially defined tissue domain?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where within a tissue do cells of a specific type express a gene of interest, and does this depend on spatial position?
View paper
Yang J. et al. - 2024

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially variable marker genes show expression patterns that align with known anatomical zonation in the tissue?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What molecular pathways are dysregulated in spatially variable genes identified in a disease tissue?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatial co-expression patterns exist between pairs of genes within a tissue section?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell-cell communication signals are strongest in a specific condition?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : LatentScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the composition and proportion of cell phenotypes differ between healthy and chronically inflamed tonsils?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which proteins exhibit opposing spatiotemporal expression patterns among the most significantly differentially expressed proteins?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 2D spatial distribution of cell types in tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the histologically annotated tissue regions of a pancreatic ductal adenocarcinoma sample?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial boundaries between tumor and tumor edge regions?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What biological functions are enriched in spatial domains?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains identified by computational analysis of the tissue?
View paper
Kambhampati S. et al. - 2025

TissueMosaic: Self-supervised learning of tissue representations enables differential spatial transcriptomics across samples

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatial patterns of cell type composition, model-predicted age, and gene expression co-vary across tissue samples of different ages?
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the single-cell resolution spatial distribution of cell types in the tissue, and how does it compare when aggregated into spot-level proportions?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the rare cell's types located?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue regions distributed across a tumor section?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What are the characteristic gene expression profiles of transcriptionally distinct spatial domains in a tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : DendogramChart Type : Stacked bar chartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does tumor subclone composition and diversity vary across distinct anatomical structures within a tissue?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are total transcript counts distributed across spatial locations in a tissue section?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are known anatomical regions distributed spatially across an olfactory bulb tissue section?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell clusters spatially distributed across a tissue section?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
Do computationally identified spatial domains in the embryonic heart correspond to known anatomical cardiac structures?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell types in a whole organism?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cell cluster based on gene expression similarity?Where are the different cell types located within the tissue?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which cell types are spatially co-localized in the developing heart, suggesting potential cell-cell interactions?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is cellular heterogeneity distributed across the spatial extent of a tumor tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types preferentially co-localize in space within a tissue?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do gene contributions relate to gene set membership?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a differentially active pathway spatially distributed in tissue?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are differentially expressed across spatial regions of a tumor?
View paper
Yuan et al., 2020

GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do the spatial expression patterns of a predicted ligand-receptor pair show co-localization in tissue?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific signals localized within spatial structures?
View paper
Yuan et al., 2020

GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do the spatial expression patterns of a predicted ligand-receptor pair show co-localization in tissue?
View paper
Kamel M. et al. - 2024

SpatialOne: end-to-end analysis of visium data at scale

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial expression pattern of a cell-type marker gene across a tissue section?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotChart Type : Spatial gridChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what is the full cell type composition at individual locations?
View paper
Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does displaying gene colocalization and spatial domains side-by-side make their relationship interpretable?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of spatial neighborhoods for diseased cells?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does biconvolution with directional quaternion kernels reveal spatial boundaries in transcriptomic data?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Which cell types exhibit the strongest or most frequent communication interactions within the tissue?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which combinations of anchor and neighbor cell types show the greatest number of interaction-context-dependent genes?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
What connectivity patterns exist between identified domains?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological pathways or functions are significantly enriched in genes that define a specific spatial tissue domain?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which communication signals are strongest and shared across samples?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Bar plotChart Type : BoxplotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are upregulated or downregulated along a developmental trajectory and what biological processes do they represent?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How well do methods identify spatial domains=
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the ground truth laminar organization of the cortex?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularAbstraction : PartialChart Type : ScatterplotChart Type : Violin plotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does protein expression vary across spatial positions?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do genes with significant spatially varying expression have residual spatial patterns that are not explained by cell type composition?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Do the molecular factor of a cell type co-vary with the molecular factors of specific neihboring cell types? Are any potential co-regulated signaling loopd?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What disease associations characterize molecular spatial domains?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How does a gene's three-dimensional expression pattern relate to the spatial distribution of its associated cell type in a reconstructed embryo?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do astrocytes with different cellular neighbors show spatially distinct gene expression patterns within the same tissue?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which multi-hop communication pathways are most frequent?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Microscopy imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific co-expressed gene modules active, and do they correspond to cell subpopulations?
View paper
Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can multiple biological dimensions be simultaneously visualized in spatial transcriptomics data without loss of interpretability?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Data Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological structure of the tissue being analyzed by spatial transcriptomics?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes exhibit spatially organized expression patterns?
View paper
Liu W. et al. - 2024

SpaGIC: graph-informed clustering in spatial transcriptomics via self-supervised contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which are the spatial domains in the tissue and related marker genes?Which are the spatial domains in the tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Does total gene expression density reveal tissue structure ?What cell types are present in a fraction of tissue?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue morphology and expert-annotated layer structure look like in a reference sample?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are selected genes spatially expressed?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do marker gene expression differ across spatial domains?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Violin plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes differ in expression between spatial domains?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in the top-ranked sensitive genes from the communication analysis?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do anatomical brain structures vary across sequential coronal sections through the brain?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell clusters spatially located in the organism?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the organization of the cells?
View paper
Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Modality : GenomicsOther : UI / Screenshot
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Does a known regional marker gene confirm the presence of a specific cell type in a region?
View paper
Preibisch S. et al. - 2025

Scalable image-based visualization and alignment of spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the three-dimensional spatial expression pattern of specific genes across reconstructed tissue sections?
View paper
Larsson L. et al. - 2023

Semla: a versatile toolkit for spatially resolved transcriptomics analysis and visualization

Other : UI / Screenshot
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell populations of interest spatially distributed across two comparable tissue datasets?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Do DCIS/LCIS clusters show distinct hallmark pathway enrichment profiles compared to IDC clusters?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial expression patterns of genes identified as spatially variable?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is cell type composition spatially distributed across a cortical tissue section?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which cell-cell communication pairs are dettected?Which ligan-receptor pairs show spatially resolved communication between cell types?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do observations group by molecular similarity?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct anatomical regions spatially organized within a tissue section?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are molecularly defined subregions distributed across anatomical regions?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the expression pattern of marker genes?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How do metagene expression patterns correlate with biological pathways?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do prostate cancer clusters separate from non-cancer clusters in UMAP embedding space?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the cell types proportions?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different tumor subtypes and tissue states distributed spatially within a cancer tissue section?
View paper
Mohanty C. et al. - 2024

SpatialView: an interactive web application for visualization of multiple samples in spatial transcriptomics experiments

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : No abstractionAbstraction : PartialChart Type : HeatmapChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Does a gene of interest show differential expression across clusters and between sample groups?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in spatially defined gene co-expression clusters in a disease tissue context?What biological processes are enriched in the gene sets defining each spatially distinct co-expression cluster?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of gene co-expression modules?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Do the marker genes identified for different gut regions show region-specific co-expression patterns?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the cell type identities present across the tissue?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Dot ChartChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial localization and expression correlation between markers in both healthy and diseased tissues?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes are significantly upregulated or downregulated in specific cell types in regions with high pathological burden?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes differ between cell states?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
How spatially enriched are different astrocyte subtypes in proximity to each other?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : CellularBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How predictive is the neighborhood cell composition for determining the central cell's identity across all detected cell types?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : PseudotimeModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Is there a continuos transcriptional gradient between different tissue domain types?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How does the distribution of subcellular localization labels per gene compare across cell lines?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are most differentially expressed between spatially defined tissue domains?
View paper
Sriworarat et al., 2023

Performant web-based interactive visualization tool for spatially-resolved transcriptomics experiments

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Density PlotChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are spatially resolved gene expression measurements distributed across a tissue section?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How does inferred cell state progression distribute across cancer sub-populations in embedding space?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
Do different marker genes show distinct spatial expression patterns across the 3D tissue?Where in the 3D tissue is a specific gene expressed?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : ProteomicsVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What cell types are present in the tissue?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How many cells have more probability to being part of a tumor?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Which spatial domains are present in the tissue?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are differentially expressed across distinct cell types as identified by computational cell typing?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial expression gradients relative to tumor boundaries?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tissue sections spatially organized in 3D?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Do co-expression gene modules display spatially distinct patterns within a specific cell population?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are cell types spatially organized in the cerebral cortex?
View paper
Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types organized across the tissue?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical layers in the tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What genes most strongly define the identity of a specific tissue region or cell population?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalData Components : StatisticModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : RelationshipBiological : MolecularBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Are the transcripts of module genes more physically proximal to each other in diseased cells compared to healthy cells?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially arranged in the tissue?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : StatisticMetadata : Experimental : Treatment groupResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Space-fillingScalability Strategy : Sampling/Filtering
How do features differ across conditions?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are differentially expressed in a specific cell type between different spatial microenvironments?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What genes are differentially expressed across spatial neighborhoods?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Network graphChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Do cell clusters from the reconstructed communication graph form interpretable groupings in low-dimensional space for the dataset?
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Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
Which spatial regions and time points contribute moststrongly to each latent pattern of gene expression variation?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Alluvial plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs most strongly mediate communication between two specific cell types, and which are uniquely identified by the proposed method?
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Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Space-fillingScalability Strategy : Summay/Aggregate
What cell types make up each spatial region?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Network graphChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are cell-cell communication interactions spatially localized?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of downstream signaling pathway activity?
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Morabito S. et al. - 2023

hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial gridChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do transcriptomically defined clusters map onto anatomical regions of a tissue in spatially resolved transcriptomics data?
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Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does pathway activity in different cell types vary based on spatial proximity to another cell type?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do anatomical structures change across developmental stages?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Do known Alzheimer's Disease (AD) related genes feature more frequently in the detected functional modules in AD mouse models compared to healthy controls?
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Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Whisker plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does the expression level or association score of interaction-dependent genes vary across different cell-type pair contexts?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Data Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Spatial gridChart Type : Spatial HeatmapChart Type : Violin plotChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes distinguish spatially defined tissue regions, and what is the magnitude and significance of their differential expression?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Which cell types communicate?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do gene expression patterns corresponds with cell cluster?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Space-fillingScalability Strategy : Summay/Aggregate
How does the cell type composition differ across spatial tissue domains?
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Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteAbstraction : PartialChart Type : Network graphChart Type : Schematic anatomical diagramCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Which cell type clusters are anatomically adjacent in brain tissue, and how does that adjacency structure inform color assignment evaluation?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do identified colocalized gene pairs show visually apparent spatial co-occurrence within specific subcellular compartments?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where is a specific marker gene expressed within the spatial layout of a tissue section?
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Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Data Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
General research question ★ How do independent components associated with distinct tumor and stromal cell types distribute spatially across a cancer tissue section?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific spatially variable genes expressed, and do their expression patterns reflect distinct tissue compartments?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially arranged within a tumormicroenvironment in a given sample?
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Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the expression pattern of marker genes?
View paper
Bao et al., 2025

Spatially informed graph transformers for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains, their marker gene expression, and correspondence to reference atlases?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Data Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells cluster according the transcripts?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are specifically expressed in each spatial domain of a tumor tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What cell types are present in a fraction of tissue?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotChart Type : Line ChartCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What biological pathways are enriched in cells with high importance scores for a specific gene?
View paper
Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Immunofluorescence imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the known layered architecture of a tissue, as seen in a fluorescence microscopy image?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
What are the connectivity relationships and potential transitions between identified domains?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial expression patterns are characteristic of genes exclusively identified as spatially variable by a specific method?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
In which cell types is a receptor gene most highly expressed?
View paper
Niu J. et al. - 2025

SpatialCVGAE: Consensus Clustering Improves Spatial Domain Identification of Spatial Transcriptomics Using VGAE

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show spatially variable expression patternsacross a tissue section?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are significantly associated with a biological trajectory, and in which direction?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Clinical dataData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/Filtering
How does marker gene expression is related with the survival outcomes?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial density distribution of an ossification marker gene?
View paper
Andersson A. et al. - 2024

Points2Regions: Fast, interactive clustering of imaging-based spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : TissueAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/Filtering
Which gene pairs show consistent co-expression structure across PDAC tumors?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/ACondition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Bar plotChart Type : Dot ChartChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What genes and biological pathways characterize a spatially distinct cell cluster, and where does it localize within the tissue?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a pathway?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue do specific spatial clusters appear across multiple coronal brain sections?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How does the computational method identify cancer tissue heterogeneity?
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Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the number of condition-specific cell-cell interaction genes differ between disease and control groups across cell type pairs?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
which spatial domains exist in this tissue section?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & Signaling
What cell-type-specific communication occurs between microglia and excitatory neurons locally?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the spatial proximity distance between the different markers?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tumor and non-tumor regions spatially delineated in a cancer tissue section?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are shared and patient-specific transcriptional states spatially distributed across different tumor samples from distinct patients?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
what is the full cell type composition at individual locations?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What transcriptional cell types exist in the data?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are spots meeting a specific expression criterion located within the tissue?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the main biological function associated with the marker genes?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in the gene sets defining each spatially distinct co-expression cluster?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are different cell types spatially located within multiple tissue regions?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do molecular spatial domains relate?
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : 3D surface mapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the three-dimensional spatial organization of cell types or brain regions in the mouse brain as measured by volumetric in situ sequencing?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes show significant cell-type-specific differential expression across spatial regions, and in which cell types is the effect strongest?
View paper
Liu T. et al. - 2024

Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell type distribution in the tissue?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of specific genes across the tissue?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial domain structure is identified in mouse coronal brain tissue?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial distributions of marker genes?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designScalability Strategy : Summay/Aggregate
How do cell-cell interaction patterns differ within and between spatial communities?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How strong and statistically significant is the predicted communication through a specific ligand-receptor pair between two cell populations?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological reference architecture of the mouse kidney?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : SimulatedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do transcriptomic profiles vary across spatial locations when projected into a low-dimensional embedding space?
View paper
Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell clusters spatially organized in tissue?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What is the spatial expression pattern of marker genes in tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Which transcriptional states are shared across multiple tumor samples and which are unique to individual patients?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Where are the co-expression modules between spatially variable genes?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific signals localized within spatial structures?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial expression patterns of genes identified as spatially variable exclusively by a given method?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatially distinct gene co-expression patterns are in lung cancer tissue?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do predicted spatial locations of cell subtypes match the observed expression of their defining marker genes?Where in the tissue are different subtypes of a given cell class spatially located?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteAbstraction : PartialChart Type : BoxplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How does the spatial distance of a cell type from a tissue landmark vary across anatomically distinct tissue zones?
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Kambhampati S. et al. - 2025

TissueMosaic: Self-supervised learning of tissue representations enables differential spatial transcriptomics across samples

Condition Dimension : N/AData Components : Biological AnnotationData Components : Clinical dataData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatial patterns of cell type arrangement and cellular purity differ between structurally normal and disrupted tissue units?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Which spatial locations exhibit the largest deviation in transcriptomic profile when a directional rotation is applied?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How are tumor cell subclones distributed in transcriptional similarity space?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Does the abundance of an immune cell subtype differ significantly across tumor regions?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
Which transcripts show significant spatial co-expression relationships?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/Filtering
Which ligands show correlated expression patterns?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially organized within the tumor microenvironment?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial organization of cell types in diseased tissue?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do marker genes for a given cell type show spatially concordant expression patterns with the predicted locations of that cell type?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do subcellular RNA distribution domains appear when visualized directly from single-molecule spatial data compared to their computational abstractions?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the fine-grained spatial expression pattern of a gene within a specific tissue subregion?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
What is the three-dimensional organization of transcriptionally defined spatial domains across stacked tissue sections?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How effectively can different gene sets identify tumor boundaries?
View paper
Avesani S. et al. - 2022

Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do computational clusters correspond to pathologist annotations?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Alluvial plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs most strongly mediate communication between L6 CT and L6 IT neurons in the cortex, and which are uniquely identified?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is a tissue functional signature score distributed across the spatial extent of a tissue section?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in tissue space are the cells that most strongly drive classification of a particular cell type?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What genes are differentially expressed between cell states?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are specific cell types spatially organized in supervised cell type assignment?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Sankey diagramCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
How do extracellular ligand-receptor signals connect to downstream intracellular transcription factor activation within a receiving cell?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : CategoricalCondition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : ProteomicsResolution of observation : CellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
how does cellular composition vary across different samples?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What are the major co-expression domains present in the tissue, and how are they spatially organized?What does the tissue look like at the histological level, and where are the major anatomical features located?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the estimated spatial expression pattern of a second gene of interest evolve over disease progression time points?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What biological processes and molecular functions are over-represented among genes that show spatially variable expression across tissue regions?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a principal component vary across tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How do copy number variation profiles differ across tumor cell subclones?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : UpSet plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How are subcellular localization labels distributed and co-assigned across transcripts in a given cell line?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially detected domains correspond to regions with distinct marker gene expression patterns?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
identify cells with shared functional patterns
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How strong and statistically significant is the predicted communication through a specific ligand-receptor pair between two cell populations?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Does the low-dimensional representation learned from spatial transcriptomics data capture both cell type identity and regional tissue structure simultaneously?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which gene sets are enriched in each domain?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Are the ligand and receptor of a signaling pair expressed in complementary cell populations, suggesting potential cell-cell communication?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Topology plot (2D)Communicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the key markers located in healthy and diseased tissues?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What is the predominant subcellular localization pattern for each gene, and how consistently is it assigned across cells?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the anatomically defined layers of the cerebral cortex and how are they spatially arranged in a reference brain section?
View paper
Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of the SVGs across the dataset?
View paper
Bao et al., 2025

Spatially informed graph transformers for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical spatial domains in tissue (ground truth)?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

General Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition Comparison
How do different methods integrate epigenome-transcriptome data?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which are the cell types present? Do they match the observed expression patterns of their marker genes?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do spatial domains identified by the method form coherent, separable clusters in low-dimensional embedding space?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Can a continuous color encoding capture the transcriptional landscape of a complex tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How similar or co-occurring are different cell types across spatial locations in the tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedModality : Sequencing-basedResolution of observation : Multi-cellularBiological : CellularBiological : TissueAbstraction : CompleteChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designScalability Strategy : Summay/Aggregate
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a specific transcript in tissue?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivitySpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are uniquely or commonly enriched in condition-specific versus constitutively expressed genes?Which genes are stably expressed across conditions (constant markers) and which are specifically upregulated only under certain conditions (conditional markers)?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How do cell types interact, and which signaling pathways mediate those interactions?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do genes cluster based on their expression patterns in reduced dimensional space?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the known anatomical organization of the region of interest in a reference brain atlas?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What cell types are present in the tissue?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial domains in the tissue?
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Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What biological pathways differ between spatial domains?
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Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What functional categories of genes are most commonly identified as interaction-context dependent in spatial transcriptomics data?
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Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What are the relationships between the pairs of different cell clusters in healthy and diseased tissues?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are overrepresented among genes associated with a specific cellular or tissue response?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are immune cell states spatially distributed relative to tumor cell density in a tissue section?
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Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How can a virtual cross-sectional slice be extracted from a 3D reconstructed tissue volume to reveal internal neuronal distributions?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
How are different cellular neighborhoods distributed across the spatial network, and does proximity in the network reflect likelihood of cell-cell interaction?
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Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does cell type spatial organization vary across tissue depth?Where are specific genes expressed within the tissue architecture?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the spatial organization of a tissue region look like, and where are its anatomical compartments located?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Radial PlotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : CircularScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the spatial distribution of cells with the identified functional pattern across the entire tissue?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Spatial gridChart Type : Spatial HeatmapChart Type : Violin plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Where are specific genes expressed spatially, and how do their expression levels differ across tissue domains?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the spatial distances between different cell neighborhoods?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Are the cells expressing a ligand and the cells expressing its receptor spatially adjacent in tissue?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What is the proportions of cells that are expressing different levels of pathway activities?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Are specific cell types spatially co-localized or segregated from one another at different distances?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : StatisticModality : SimulatedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellullar composition of spatially defined tissue regions?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial domains based on histology?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Violin plotComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does protein expression vary across histological domains?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the activity of a gene co-expression module vary across cells in both transcriptional and physical tissue space?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a diseased tissue section?
View paper
Pardo B. et al. - 2022

spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a specific gene across a tissue section?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Are the ligand and receptor of a signaling pair expressed in complementary cell populations, suggesting potential cell-cell communication?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What distinct spatial expression domains does stIHC identify in the mouse brain, and which genes characterize each domain?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the known laminar organization of a tissue structure as visualized by imaging?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs mediate communication from a specific cell type outward to its niche neighbors?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : AnnotationLayout : LinearScalability Strategy : Summay/Aggregate
What is the cell type composition of each spatially defined domain in the embryonic heart?
View paper
Morabito S. et al. - 2023

hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial gridChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the activity of a co-expression module vary spatially across a tissue section?
View paper
Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can spatial domain boundaries be communicated without occluding other spatially encoded variables?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where in diseased tissue are predicted directional ligand-receptor interactions occurring between specific cell types?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do transcriptionally defined clusters correspond to spatially coherent regions in the tissue?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the expert-defined spatial boundaries of pathological regions in a tumor tissue section?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What gene signature characterizes specific anatomical structures?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How do gene expression levels associate with patient survival outcomes?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatial feature intensities vary across conditions?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of each cell type's spatial neighborhood?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the raw spatial coverage?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteAbstraction : No abstractionChart Type : Histological imageChart Type : Line ChartChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Does spatial proximity between ligand- and receptor-expressing cells support a predicted cell–cell interaction?
View paper
Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes are significantly diferentially expressed between two spatial tissue domains?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are functional gene signatures spatially distributed in tissue?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the spatial domains in the tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does supervised cell type assignment map spatially in tissue at subcellular resolution?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Dot ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do distinct cell state trajectory branches correspond to spatially segregated regions within a tissue?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific marker genes expressed in tissue?
View paper
Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How does the spatial distribution of specific cardiac cell types change across developmental stages of the embryonic heart?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Were are the cell clusters located?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
Does a gene's spatial expression pattern in tissue match its expression pattern in single-cell data?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : DendogramChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Which genes show the highest differential expression across tissue spatial domains?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
Where are specific genes expressed in tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What is the distribution of gene expression values among spots in a selected tissue region?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where is a specific marker gene expressed in tissue?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do marker genes for a given cell type show spatially concordant expression patterns with the predicted locations of that cell type?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the direction and magnitude of expression gradients?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue look like at the histological level, and where are the major anatomical features located?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which oncogenic hallmark pathways are enriched across different clusters?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are spots meeting a specific expression criterion located within the tissue?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What are the expression patterns of functional genes across spatial domains?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedModality : ProteomicsResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes serve as markers for distinguishing identified cell populations?Which proteins distinguish identified cell clusters?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What transcriptionally distinct cell populations can be identified across multiple tumor samples when analyzed together in a unified embedding?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes and pathways characterize spatially distinct clusters in BRCA tissue?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : LatentScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the composition and proportion of cell phenotypes differ between healthy and chronically inflamed tonsils?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the gross tissue morphology look like in the sample being analyzed?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
DOes the gene expression correspond with the histologically observable cell-level structures?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a mathematical rotation transform the spatial color distribution of transcriptomic data across the tissue?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does spatial filtering identify marker genes whose expression pattern matches the geometry of a local transcriptomic neighborhood?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How big is the difference between the prescence of marker genes in healthy and diseased tissues?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do molecular expression patterns align with morphological tissue features?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does spatial smoothing clarify the underlying continuous expression domains of co-expression modules compared to unsmoothed spot-level maps?What are the average spatial expression patterns for each co-expression module at the native measurement resolution?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : Biological statusMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial extent or character of a tissue injury region change over time during regeneration?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the expression of groups of genes changesystematically as a function of distance from an anatomical boundary?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the temporal expression pattern of a gene cluster along a developmental trajectory?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Are distinct cell types well-separated in the transcriptional embedding learned by a spatial integration method?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are specifically expressed in each identified spatial domain?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Violin plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes differ in expression between spatial domains?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How are transcriptionally similar spots grouped in low-dimensional embedding space, and which clusters share similar expression profiles?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do pathway activities differ between spatially defined tissue regions?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the defined anatomical regions in the reference atlas?
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Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What genes are differentially expressed between functional immune cell states in distinct tumor regions?
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Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial expression pattern of a functional gene signature?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched among the most significant genes in the Visium cortex communication analysis?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueAbstraction : PartialChart Type : Spatial gridComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
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Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial distribution of immune cell abundance compare across biological conditions in tissue sections?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are specific cell populations spatially distributed ?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which communication signals are strongest across the entire tissue?
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What does the spatial distribution of cell types look like in the tissue fields of view where color differentiation is most critical?
View paper
Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Half violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How is gene expression distributed across cell clusters?
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Gong C. et al. - 2024

SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where within a tissue section is a given gene expressed, and does its spatial distribution reveal region-specific patterns?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does gene expression vary spatially across tissue sections before and after alignment?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How many spatial domains are present in the tissue?
View paper
Morabito S. et al. - 2023

hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Bar plotChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Sampling/Filtering
How are genes organized into co-expression modules, and which genes serve as hubs within those modules?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are computationally defined cell types or clusters distributed spatially across a tissue section?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartChart Type : Radial network plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : CircularLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the target genes of a transcription factor regulatory network change across developmental time?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell clusters spatially distributed across a tissue section?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Alluvial plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs most strongly drive communication between astrocytes and inhibitory neurons, and which are uniquely identified by this method?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivitySpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Bar plotChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in the differentially expressed genes of each cell type within a tissue region?Which genes are differentially expressed across cell types within a spatially defined tissue region?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What biological pathways differ between expression programs?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where do major cell types spatially co-localize within a tumor?
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Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : StatisticModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What is the variability in spatial patterning scores across gene family members?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How is module expression distributed spatially in cellular environments?
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Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are normal, pre-invasive, and invasive tumor regions spatially distributed in a breast tissue section?
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Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial distribution of cell types in tissue?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial arrangement of annotated tissue layers in a brain section?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

General Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature Expression
qp?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial boundaries of pathologically distinct tissue regions in a tumor section?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : Linear
What is the gene expression profile of cellular environments?
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Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Other : UI / Screenshot
View paper
Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : UpSet plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which cell-cell interaction marker genes are consistently identified across multiple samples, and which cell type pairs do they associate with?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are different spatially informed cell types located within the tissue?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What histological regions define the tissue?
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Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
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Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where is specific pathway activity spatially localized in the tissue?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially organized across a brain section?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What is the expression pattern of marker genes?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularAbstraction : PartialChart Type : Spatial gridChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does a gene's spatial expression pattern appear when visualized on a cross-sectional plane through the reconstructed 3D brain volume?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : 3D mapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
How do spatial gene expression, regulatory programs, and cell-cell interactions integrate across multiple scales of biological organization in a 3D tissue?
View paper
Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes expressed in a focal cell type show significant associations with the composition of neighboring cell types?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can the annotation being tranferred across developmental time?Is it possible to analyze cell type spatial dynamics=
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the area of key markers compare between healthy and diseased samples?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell types show the most statistically significant transcriptional differences between spatially defined tumor regions?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue is a specific gene expressed, and does its spatial distribution correspond to known anatomical boundaries?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can spatially resolved reconstruction of marker gene expression improve the alignment between transcriptomic signals and histologically defined tissue structures?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does spatial transcriptomics clustering resolve the laminar structure of the cerebral cortex?
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Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the marker genes for each spatial domain?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the major structural regions within the tissue and where are they located?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are most highly expressed within a computationally identified spatial domain, and do they represent biologically meaningful markers for that region?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do predicted spatial locations of cell subtypes match the observed expression of their defining marker genes?Where in the tissue does a specific subtype marker gene show expression within a defined cell population?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : Bar plotChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are spatially variable genes expressed across cortical layers, and in what proportion of cells within each layer is expression detected?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Are known marker genes selectively expressed in their expected tissue layers or domains?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do annotated cell types separate in a low-dimensional transcriptomic embedding of highly variable genes?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domain clusters in the dataset?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a highly spatially variable gene across a tissue section?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the spatial distance from a reference cell type vary across different cell populations in tissue?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Which cell types are present?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : ProteomicsResolution of observation : Field of viewVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does cell type composition vary across different tissue regions?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can spatially coherent regions of interest be identified and delineated within a tissue sample?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What gene signatures characterize different tumor spatial neighborhoods?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the functionally distinct spatial domains based on gene co-expression?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What are the developmental trajectories? Does CCSF preprocessing improve PHATE's ability to reveal cell developmental trajectories and branching compared to standard methods?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : CategoricalData Components : StatisticMetadata : Experimental : DonorModality : ProteomicsResolution of observation : CellularVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do pairwise relationships between cell types differ between patients conditions?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures in the reference atlas?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific signals localized within spatial structures?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct cell types distributed across the spatial extent of a tumor tissue?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesChart Type : Half violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How are neighborhood marker genes expressed at single-cell resolution?
View paper
Sottosanti et al., 2021

CO-CLUSTERING OF SPATIALLY RESOLVED TRANSCRIPTOMIC DATA.

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the regions present in the tissue?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs mediate communication between cell types?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Radial PlotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : CircularScalability Strategy : No scalability strategy (Item-level)
Are the genes in the module expressed at higher levels in specific subcellular regions compared to other genes?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the spatial expression pattern of specific genes change between two biological conditions?
View paper
Madhu et al., 2025

HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Space-fillingScalability Strategy : Summay/Aggregate
Do transcriptional sub-populations within a cell type differ in their spatial microenvironmental context?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do computationally detected spatial domains correspond to transcriptionally distinct cell populations?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How do the spatial distributions of hippocampal neuron subtypes align with established anatomical hippocampal subregions in a standard atlas?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Square bubble PlotLayout : LinearScalability Strategy : Summay/Aggregate
What are the biological processes that characterize the overall cell type identity of the cells belonging to the discovered module?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial distribution of cell-type compositions across different tissue samples and does it align with known layer annotations?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains in the tissue?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Is the apparent spatial variability of a gene driven by cell type composition differences across the tissue rather than genuine within-cell-type expression variation?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : Force-directedScalability Strategy : Summay/Aggregate
How are enriched gene sets related to each other?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Network graphChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which cell types are predicted to interact via a specific ligand-receptor pair, and what does their spatial co-localization look like?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cancer sub-populations separate in low-dimensional embedding after sub-clustering?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do samples from different donors or batches cluster separately before data integration?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : 3D ScatterplotChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What are the spatial domains in 3D?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell-cell communication signals are most abundant in a specific tissue region
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Metadata : Experimental : SampleModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do near-cellular-resolution spatial clusters correspond to known anatomical brain subregions, and how do they organize in latent space?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes distinguish different cell types in pancreatic cancer tissue?
View paper
Hägele et al., 2024

Visual Compositional Data Analytics for Spatial Transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Stacked area chartCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Space-fillingLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do spots with similar cell type composition form coherent groups in reduced-dimensional space?Where on the tissue are specific cell type proportion patterns located?Which k-means cluster groupings of cell type proportion patterns are present and selectable for comparison?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
Which cell types are present?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which multi-hop communication pathways are most abundant?
View paper
Ma Y. et al. - 2024

HyperGCN: an effective deep representation learning framework for the integrative analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene expressed across the tissue?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Violin plotChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What genes are differentially expressed between spatial domains?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
What is the expression level and spatial position of an individual spot in a tissue?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionAbstraction : PartialChart Type : Bar plotChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What are the main differences by cellular and structural markers between healthy and disease?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotChart Type : HistogramCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which ligand-receptor pairs show conditional correlation?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do annotated anatomical regions map onto the spatial layout of a tissue section?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does a marker gene's spatial expression pattern agree with the computationally estimated distribution of its associated cell type?
View paper
Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells cluster according the transcripts?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the spatially defined interaction zones located within the tissue section?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesScalability Strategy : Summay/Aggregate
How do cell-cell interaction patterns vary across spatial comunities?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What is the three-dimensional spatial organization of distinct hippocampal neuron subtypes across the reconstructed brain volume?
View paper
Hakobyan S. et al. - 2025

Topology-aware pathway analysis of spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially resolved pathway activity scores agree in their tissue-level spatial distribution?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DData Components : TimeModality : Imaging-basedVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do cell populations shift spatially and transcriptionally across developmental time points?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tumor tissue are cancer cells at early vs late stages of a differentiation trajectory?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are specific cell types distributed?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How are cancer molecular subtypes distributed across spatial tumor domains?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : CategoricalData Components : StatisticModality : Sequencing-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What pathways define a cell cluster?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : ProteomicsVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What functional zones exist within a specific tissue region and how are they organized?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do predicted cell types form well-separated clusters in gene expression space?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do spatially derived imaging features reflect the transcriptional activity of their corresponding genes within the same tissue region?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
How do genes within a biological theme interact?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How does the 3D distribution of transcriptomically similar cells within a whole-brain volume reflect the spatial extent of specific gene expression programs?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what is the spatial distribution and co-localization pattern of multiple proteins within a tissue region?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : 3D ScatterplotChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
How do the transcriptomic profiles of neighboring spots vary spatially across a tissue section?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which communication signals are strongest and shared across samples?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are specific cell populations spatially localized within a 3D reconstructed tissue volume?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What are the spatial relationships between cells in tissue?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does cell density vary spatially?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : TimeMetadata : Experimental : Biological statusModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does a gene expression program change in activity acrossdevelopmental time points?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types distributed across tissue?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are hippocampal subregions spatially arranged in a reference brain section, and what are their anatomical boundaries?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Simplex-based scatter plotChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are multiple IC signals distributed spatially across a prostate cancer tissue?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Ho does spatial proximity between specific cell types vary across individual cells within a tissue region?
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Condition Dimension : N/AModality : scRNA-seq
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : TimeModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Violin plotComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do distinct cell subtypes within a population show different levels of a transcriptional program?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the gene expression signatures differ across tissue regions?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial distribution of cell subclasses across a tissue section?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of different cell types ?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : No abstractionAbstraction : PartialChart Type : Bar plotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How are the marker genes distributed in the space in the context of knn distance?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do cortical layer-specific marker genes show selective expression in their expected layers when identified by spatial transcriptomics?
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Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which cell types are present?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the spatial distribution of tumor cell proportions?What is the spatial organization of tumor progression states?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the major anatomical regions in the tissue?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can dimensionality reduction of spatial transcriptomic data reveal transcriptionally distinct cell populations within their native tissue context?
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Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
What are the dominant directional communication relationships between cell types in the hypothalamic preoptic region?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where is specific pathway activity spatially localized in the tissue?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in tissue space are cells with high vs low estimated expression of a specific protein?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designScalability Strategy : No scalability strategy (Item-level)
What cell types are present?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does gene expression varies across clusters?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do transcriptomically defined cell clusters form spatially coherent groups within a tissue section?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
How are different cell types distributed in 3D across stacked tissue sections?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : StatisticModality : SimulatedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellullar composition of spatially defined tissue regions?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial distribution of cell types vary across different tissue samples and time?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : No abstractionAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do identified embryonic tissue domains express known organ-specific marker genes?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are chondrocytes and ossification-related cells spatially organized?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial expression pattern of a gene detected computationally compare to its known in situ hybridization signal in the same tissue?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial domains in the tissue?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is a specific cell type distributed relative to spatial community borders?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the spatial distances between cell neighborhoods and reference cell types?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is cell type composition distributed across spatial locations in cerebellar tissue?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does a gene show spatially varying expression within a specific cell type across anatomically distinct tissue regions?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures present across different tissue preparation methods?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Histological imageChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the anatomical structures of the tissue?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : CategoricalData Components : StatisticModality : Sequencing-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What pathways define a cell cluster?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
What does the tissue morphology look like at higher magnification for a region of interest within a spatial transcriptomics section?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Sankey diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designScalability Strategy : No scalability strategy (Item-level)
How are cell–cell communication signals distributed between sender and receiver cell types across different spatial regions of the tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
What is the estimated spatiotemporal expression pattern of a specific protein across the tissue network?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which gene correlations show heterogeneity across tumor samples?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : No abstractionChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cell types distribute in the tissue?What cell types are present in the tissue?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial HeatmapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the ground truth spatial organization ?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What is the realtionship between 2 differents pathways expressed across the cells?
View paper
Qing J. et al. - 2025

SCNT: an R package for data analysis and visualization of single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a specific gene within a tissue region?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do spatially defined tissue domains, identified by cellular composition, partition across a tissue section?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial extent of a specific subregion of interest?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are transcriptionally distinct tissue regions distributed spatially in a cancer tissue section?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How many differentially co-expressed genes are contained within each of the identified gene modules?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of specific genes across the tissue?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the pattern expression of the known marker genes?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are spatial regions organized across conditions?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the ground truth spatial organization ?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cancer-associated spot clusters separate from non-cancer clusters in low-dimensional embedding space?
View paper
Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell clusters spatially organized in tissue?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Does the cellular neighborhood of a cell type affect its gene expression profile, and which genes show the strongest environment-dependent variation?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteAbstraction : PartialChart Type : HexplotChart Type : Violin plotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do interaction zone spots at domain boundaries exhibit higher transcriptomic diversity than non-interactive boundary spots?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
What is the distance between different marker genes in healthy and diseased states?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns for a selected gene?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
Which transcripts show significant spatial co-expression relationships?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Immunofluorescence imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where is a specific brain region located within the reference atlas anatomy?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
In which proportions the cell types are present in the spatial domains?Which cell types are present?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Avesani S. et al. - 2022

Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of the genes?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell-cell communication signals are strongest in a specific condition?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns for a selected gene?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological structure of the tissue sample?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in the gene sets defining each spatially distinct co-expression cluster?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Dot ChartChart Type : Half violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes are differentially expressed across spatially defined tissue domains, and what are the top marker genes for each domain?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
How do spatial domain boundaries relate to cell type distributions?
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does an image-guided color palette perform when applied to spatial transcriptomics cell cluster visualization?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the organization of the cells?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial routes taken by different cell types during tissue development or migration?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific proteins expressed in different tissue regions?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : UpSet plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What proportion of transcripts are assigned to each subcellular localization label, and how frequently do transcripts receive multiple labels simultaneously?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which gene correlations remain after accounting for confounding variables?
View paper
Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Modality : scRNA-seqOther : UI / Screenshot
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tissue sections spatially arranged on a capture platform?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Flourescence tissue imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the morphological characteristics of tissue?Where are specific cell types spatially located in tissue based on transcript-based segmentation?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteAbstraction : PartialChart Type : Spatial Tissue MapChart Type : TableCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/FilteringOther : UI / Screenshot
What is the transcriptomic identity of a selected spot and how similar is it to known cell type archetypes within its spatial neighborhood?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical regions in a tissue section?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue do cells co-express receptor–ligand pairs, suggesting active intercellular communication?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the selected key cell types (those highlighted spatially in (b)) appear in the low-dimensional gene expression space?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes most consistently exhibit a given subcellular localization pattern across cells, and are these genes shared across cell lines?
View paper
Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological structure of the tissue sample?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns of specific gene expression in tissue?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : Latent
Which cell types are present?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : ScatterplotChart Type : Vector field plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
In which spatial direction do brain cells progress along a developmental trajectory?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : DendogramChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Do spatially differentially expressed genes form distinct spatial expression patterns that cluster together?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of specific genes across the tissue?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes show dynamic expression changes along a differentiation trajectory?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show high correlation with known anatomical layer annotations, and can they serve as spatial layer markers?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What biological functions are enriched in spatial domains?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : Ordered : ContinuosData Components : PseudotimeData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial pattern of the inferred developmental trajectories?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Do computationally identified gene clusters correspond toknown region- or layer-specific transcriptional programs?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologySpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial organization of sub-regions within a specific anatomical structure in a developing tissue?Where are different cell types spatially located within a tissue section?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the signal-to-noise ratio of gene/protein regulatory networks differ between control and perturbed conditions?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : Density PlotChart Type : HexplotChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do different denoising methods affect the distribution and spatial pattern of a marker gene?How does denoising change the spatial expression patterns of marker genes?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a pathway?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do genes cluster based on refined embeddings in reduced dimensional space?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : Microscopy imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Which genes are co-expressed with a specific ligand-receptor pair?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Network graphChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are cell-cell communication interactions spatially localized?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue architecture of the tissue?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial organization of tissue layers in the sample?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which cell clusters express signatures associated with a specific cell identity or functional state?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Bar plotChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do cell-cell signaling strengths differ based on proximity to tumor cells?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial domains emerge ?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell types spatially enriched within a tissue section?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the spatially defined interaction zones located within the tissue section?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
How do gene contributions relate to gene set membership?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does a marker gene's spatial expression pattern validate the computationally estimated distribution of its associated tissue type?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does data denoising affect spatial expression patterns of marker genes?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do known layer-specific marker genes show spatially restricted expression patterns that match the anatomical layers identified by clustering?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are different cell types spatially located within a tissue section?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types preferentially interact or avoid each other in tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Is there a spatial association between immune cell abundance and a tissue functional signature score?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Space-fillingScalability Strategy : Summay/Aggregate
Which cell types are enriched in each spatial domain of a tumor tissue?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are over-represented in genes differentially expressed between two tissue domains?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of domain marker genes?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatially resolved expression patterns of cell-type-specific marker genes vary across a tissue section?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Alluvial plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs drive communication between pericytes and myofibroblasts in human intestine, and which are uniquely identified by the method?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Histological imageChart Type : Vector field plotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the directionality and strength of cell-cell communication across tissue space?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does a known marker gene show spatially coherent expression in its expected brain domain?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsChart Type : Tree plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
How do cell populations in a specific tissue lineage develop and transition across developmental time points?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression patternes of gene expression?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes are differentially expressed between anatomical subregions?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures of the tissue?
View paper
Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial layout of the tissue?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How well do spatially variable genes identified by different methods overlap with established cancer gene sets?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the spatial domains in the tissue?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : Microscopy imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene module expressed spatially in a specific cell type?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is the expression of marker genes?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Where are specific genes expressed in tissue?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do cell types cluster in molecular space?What are the spatial expression patterns of specific genes across tumor regions?What is the spatial distribution of cell types in tissue?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do interaction-context-dependent genes (ICGs) differ in their directional association scores compared to all other genes in the transcriptome?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pie ChartChart Type : Scatter pieCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do cell type compositions and their spatial distributions change across developmental time points?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
Which transcripts show significant spatial co-expression relationships?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
What cell type is assigned to a specific spot and where is it located in the tissue?
View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do the local microenvironment signaling profiles of spatial transcriptomic spots cluster in low-dimensional space?Which ligand-receptor signaling mechanisms best characterize the microenvironment of specific cell types in spatial transcriptomic data?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : 3D ScatterplotChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What are the spatial domains in 3D?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How transcriptionally similar are the spatial domains identified ?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Are the cells expressing a ligand and the cells expressing its receptor spatially adjacent in tissue?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spatially resolved transcriptomic clusters correspond to anatomically distinct regions in a tissue section?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How close are two different cell populations?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
Which biological pathways are significantly enriched in the genes identified from a spatial transcriptomics analysis?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How do specific cell-type or structure-associated IC signals localize spatially and in embedding space?Which genes most strongly define each independent component signal, and how do their loadings compare across components
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the cellular organization of a specific anatomical structure?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Does CCSF-PHATE consistently reveal developmental transitions and branching across different organoid batches better than standard dimensionality reduction methods?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a spatial domain detection method partition tumorand normal tissue regions across multiple HCC tissue sections?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types distributed spatially in a breast cancer tumor?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the inherent correlation structure within true domain and cell type annotations?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do feature values vary across categories?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How reproducible are tumor-associated transcriptional signals across different tissue sections from the same patient?
View paper
Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : No abstractionAbstraction : PartialChart Type : Flourescence tissue imageChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does the spatial similarity structure between spots reflect the known anatomical organization of a specific tissue region?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are the marker genes expressed across the tissue?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial expression patterns are captured exclusively by genes uniquely identified?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do independent components identify fine-grained tissue substructures at near-cellular spatial resolution?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : MolecularResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Cell segmentation
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionAbstraction : PartialChart Type : Bar plotChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What are the main differences by cellular and structural markers between healthy and disease?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Space-fillingScalability Strategy : Summay/Aggregate
What proportion of transcriptomically profiled cells are assigned to each hypothalamic nucleus by a spatial registration method?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of manually annotated tissue regions and cancer subtypes in the breast cancer section?
View paper
Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : No scalability strategy (Item-level)
How does parameter choice affect method performance?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial domain structure?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Geometric Proximity & Co-localizationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : No abstractionAbstraction : PartialChart Type : BoxplotChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does gene expression vary with distance from Aβ plaques?What are the spatial expression patterns of cell type-specific genes?What are the spatial expression patterns of specific genes across tumor regions?What is the spatial distribution of different cell types?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the histological structure of a cancer tissue sample look like?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene expressed in a spatial domain?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do transcriptionally distinct clusters map onto the spatial organization of a specific cortical region?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched among the spatially variable genes identified by a given method?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of gene modules?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Modality : scRNA-seq
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial distribution of the expression of a gene?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial tissue domains?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially predicted hippocampal cell type proportions co-localize with their known marker genes in the correct anatomical subregions?Which are the expression patterns of marker genes?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesScalability Strategy : Summay/Aggregate
How do cell-cell interaction patterns vary across spatial comunities?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which cell types co-express ligand and receptor genes?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the local spatial arrangement of cell types within a specific tissue subregion?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which is the cell type density in the tissue?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched among the most important genes identified in cell-cell communication analysis?
View paper
Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Condition Dimension : N/AModality : scRNA-seqOther : UI / Screenshot
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How domain-specific are the identified spatially variable genes?
View paper
Kamel M. et al. - 2024

SpatialOne: end-to-end analysis of visium data at scale

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological appearance of the tissue section used for spatial transcriptomics profiling?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a pathway?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What biological pathways are enriched in different cell states?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which cell types are associated with each gene module?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does neighborhood composition differ between cell states?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What transcriptional cell type structure?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a developmental or biological process vary continuously across the spatial extent of a tissue?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
What is the overall structure of tumor-immune cell interactions, and which cell types are most central in the interaction network?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Lollypop plotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do known cell type marker genes show spatially restrictedexpression patterns that align with detected tissue domains?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : SuperpositionLayout : LinearScalability Strategy : Navigating (Focus + Context)
How does the expression level of a gene vary along a defined anatomical axis of a tissue section?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
With which neighboring cell types do astrocytes most frequently co-localize, and where are these co-localizations spatially concentrated?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
At what spatial distances are specific subcellular compartments preferentially co-localized with each other?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which cell types contribute to each gene expression module?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueAbstraction : PartialChart Type : Pie ChartChart Type : Scatter pieCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell types spatially enriched across a tissue section?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seq
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent tissue domains are identified when clustering is based on cell type proportions in cerebellar tissue?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Whisker plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Does gene expression differ significantly between two spatial regions?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does local intrinsic dimensionality, at different neighborhood scales, reveal anatomical region boundaries in a spatially resolved brain section?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How can a virtual cross-sectional slice be extracted from a 3D reconstructed tissue volume to reveal internal neuronal distributions?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do specific cell types show significantly different abundances between cancerous and non-cancerous tissue regions?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where do immune cell populations localize within a tumor microenvironment?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What do tumor and non-tumor tissue regions look like histologically, and how are they spatially distributed across different patient samples?
View paper
Ma W. et al. - 2024

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial distribution of a specific cell type proportion vary across samples and biological conditions?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial boundaries and organization of anatomical regions within a tissue section?
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the spatial distribution of gene expression patterns?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How can spatially defined transcriptional domains be used to delineate biologically meaningful tissue regions?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : StatisticModality : SimulatedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellullar composition of spatially defined tissue regions?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How does tha spatial distribution of identified cell types correspond to tissue morphology?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which cell types are enriched or depleted in specific spatial domains?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Clinical dataData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains in the tissue?
View paper
Niu J. et al. - 2025

SpatialCVGAE: Consensus Clustering Improves Spatial Domain Identification of Spatial Transcriptomics Using VGAE

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are differentially expressed across spatialdomains, and do domains have distinct transcriptional signatures?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes show coordinated spatial expression patterns?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do immune subtypes preferentially localize to the outer versus central glomerular region under treatment?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Are the same genes consistently ranked as top representatives of each subcellular localization pattern across different cell lines?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : Ordered : ContinuosData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the most dynamically expressed genes change along a developmental trajectory, and what patterns of up- and down-regulation do they follow over pseudotime?
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Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue regions arranged spatially within a tumor section?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show spatial co-expression patterns with specific target genes?
View paper
Yuan et al., 2020

GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatial expression patterns of a ligand and a non-interacting receptor show less co-localization than a true ligand-receptor pair?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Where are specific genes expressed in the developing embryonic heart tissue?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatial patterns of major cell linages differ across categories?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What discrete spatial domains exist within the tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the activity of a gene co-expression module vary across cells in both transcriptional and physical tissue space?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
What is the directionality and relative strength of cell-cell communication between different cell types in the tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
What is the trajectory inference which shows the evolution from normal to diseased tissue?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteAbstraction : PartialChart Type : HexplotChart Type : Violin plotCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spots located at the boundary between tumor and adjacent tissue domains show elevated gene expression richness compared to other boundary regions?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : HeatmapChart Type : HexplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How are cell clusters spatially organized in tissue?Which specific communication signals are detected by the method?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How are cell populations spatially organized?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Lollypop plotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
In which spatial domain is each marker gene most highly expressed?Which spatial domain is most enriched for specific cancermarker genes?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent tissue domains emerge when clustering is based on cell type proportions ?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the ground-truth spatial expression pattern for each selected gene in the Drosophila embryo?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
an spatially-resolved transcriptomics identify directional progression between cancer subtypes within a single tissue section?
View paper
Guo L. et al. - 2023

VT3D: a visualization toolbox for 3D transcriptomic data

Condition Dimension : N/AData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially organized in 3D within a specific brain region?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How well does computational domain identification recapitulate known anatomical regions?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are manually annotated tissue regions spatially distributed across a pancreatic cancer section?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Where are the co-expression modules between spatially variable genes?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which genes are differentially expressed across brain regions?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific cell types predominantly located?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference tissue domain organization of a developing embryo at a given developmental stage?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalData Components : StatisticModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do genes co-occurring with a specific target gene exhibit a significantly different co-occurrence rate in the functional modules between AD and wild-type samples?
View paper
Kamel M. et al. - 2024

SpatialOne: end-to-end analysis of visium data at scale

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How does cell segmentation extend spatial transcriptomics profiling beyond the boundaries of sequencing capture spots?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which cell types contribute to each ligand module?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are differentially expressed between hippocampal subregions, and what are their relative expression patterns across subregions?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do regions of high local intrinsic dimensionality correspond to anatomical boundaries between cell subclass territories?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does unsupervised clustering identify spatial cell type patterns at subcellular resolution?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial distribution of cell types in tissue?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Which cancer subtype pairs exhibit the strongest cell-cell interaction signals within the spatially resolved tissue section?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HeatmapComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What genes are differentially expressed across spatial neighborhoods?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do raw correlations compare to conditional correlations for gene pairs?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Word CloudCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
What biological themes are represented by gene set clusters?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are most strongly and significantly differentially expressed between two groups of tissue spots?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the relative spatial distances between cell types in 3D reconstructed tissue?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteAbstraction : PartialChart Type : Network graphChart Type : Spatial Gene Expression MapChart Type : Vector field plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Where in the tissue do specific ligand-receptor signaling interactions occur between spatial domains?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Where are gene co-expression modules active within tissue structure?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is immune cell abundance spatially distributed within a tumor, and does it correlate with tumor cell gene expression?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which cell types contribute to each gene within a specific module?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the morphological characteristics of tissue?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature Expression
How does the estimated expression of a specific protein change over time across different cell types?How does the spatiotemporal expression pattern of a second protein of interest compare in its tissue distribution, cell type specificity, and temporal dynamics?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial patterns of unsupervised cell type clusters in specific organs?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : Experimental : TissueResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
Which cell types most strongly communicate with each other within a tissue niche?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : No abstractionChart Type : ScatterplotChart Type : TableCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the raw visual evidence for the subcellular location and co-localization of the module genes within individual cells?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do representative genes show spatially coherent expression consistent with their component?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial expression patterns are captured exclusively by genes uniquely identified?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is the trajectory pseudotime distributed across the tissue?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are molecularly defined subregions organized in three-dimensional space?
View paper
Xu Z. et al. - 2024

STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the spatial expression pattern of a gene change across developmental stages of the mouse embryo, and is this pattern reproducible across biological replicates?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do predicted spatial locations of cell subtypes match the observed expression of their defining marker genes?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial communities?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
Which are the marker gene expression patterns?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What are the most highly differentially expressed genes between two cell populations?
View paper
Lin Y. et al. - 2025

Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cellular morphology visible in the tissue section?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does the refined communication network differ from the raw spatial proximity graph in terms of cell-type interaction strengths?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
In which spatial tissue domains are clinically relevant receptor genes expressed?
View paper
Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed within a tissue section at single-cell resolution?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell's organization in the tissue?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific cancer hallmark gene programs active, and how are the signature genes distributed across the gene expression landscape?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Simplex-based scatter plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do features vary across abstract groups or domains?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularAbstraction : CompleteChart Type : Lollypop plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Baker et al., 2025

Morphology-Aware Profiling of Highly Multiplexed Tissue Images using Variational Autoencoders

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a highly spatially variable gene across a tissue section?
View paper
Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How is a gene's expression distributed across cell-type clusters in a low-dimensional embedding?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is a specific cell type distributed relative to spatial community borders?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which ligan-receptor pairs show spatially resolved communication between cell types?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cells organize into spatial domains?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do computationally inferred spatial clusters align with histologically identifiable tissue structures at high spatial resolution?
View paper
Velazquez D. and Fan J. - 2025

scatterbar: an R package for visualizing proportional data across spatially resolved coordinates

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Bar plotChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What is the spatial distribution of cell type compositions across tissue?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How are marker genes expressed across anatomical layers?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Linear
What are the spatial distances between cell neighborhoods and reference cell types?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What disease associations characterize molecular spatial domains?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference spatial distribution of cell types?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What cell types are present in diseased tissue?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression of selected genes?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/FilteringOther : UI / Screenshot
How does the gene expression profile of a spatial transcriptomics spot relate to the underlying tissue morphology visible by H&E staining?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What is the proportions of cells that are expressing different levels of pathway activities?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which cells in a tissue section contribute most to the model's identification of spatial cell types?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : No abstractionAbstraction : PartialChart Type : Bar plotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How are the marker genes distributed in the space in the context of knn distance?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression patternes of gene expression?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are cell types spatially organized in tissue?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial layout of hippocampal neuron subtypes on a virtual sagittal section generated from a 3D reconstructed brain volume?
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Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the spatial distribution of gene expression pattern
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What cell types are present in the tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes drive each contrastive component?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are distinct cell-cell communication networks spatially organized?
View paper
Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are multiple marker genes spatially co-distributed across a tissue at cellular resolution, and do their expression territories overlap or form mutually exclusive domains?
View paper
Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological structure of the tissue sample?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What genes define each spatially resolved cell-type domain within a tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : CircularScalability Strategy : No scalability strategy (Item-level)
What is the overall architecture and strength of the inferred cell-cell interactions within the tissue sample?
View paper
Yang J. et al. - 2024

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/Filtering
How does the expression of zonation marker genes change along a spatial tissue axis, and does this reflect known biological gradients?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent cell communities exist within the tissue?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : UpSet plotCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which biological pathways are consistently enriched among spatially variable genes across multiple individual patients with the same disease?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are diferentially expressed in cells based on their spatial relationship to another cell?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How do pathway activities vary across spatial domains?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Dot ChartComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?
View paper
Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tissue layers spatially organized across a brain section?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes best distinguish each spatially defined cell type cluster, and do their expression patterns reflect known morphological tissue regions?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D surface mapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
What does the 3D spatial structure of the tissue look like?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological appearance of the tissue section?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What functional subtypes exist within a specific immune cell population in a tumor?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the ground truth laminar organization of the tissue?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Boundary & Interface DynamicsSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
How do spatial domain boundaries relate to cell type distributions?What cell types comprise specific spatial domains?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do different clusters partition a tissue into regions?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
Which cell types are present?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are specific cell types spatially distributed across tissuesections, and do they reflect known anatomical zonation?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific pathways spatially active within tissue domains?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : Sequencing-basedVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What is the correlation between tow different pathways?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Lollypop plotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
In which spatial domain is each marker gene most highly expressed?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do specific cell-type or structure-associated IC signals localize spatially and in embedding space?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial arrangement of distinct tumor subregionswithin a tissue section?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationLayout : LinearScalability Strategy : Summay/Aggregate
What is the relationship between basal neighbord and suprabasal neighbors?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes best characterize the local transcriptomic neighborhood of a given location in the tissue?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
Which proteins show positively co-regulated spatiotemporal expression patterns among the most differentially expressed proteins?
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial domains are across multiple breast cancer tissue sections from different datasets?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the anatomical structure of the tissue?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of gene modules?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the spatially defined interaction zones located within the tissue section?
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do specific spatial domains show consistent chromosomal copy number losses, distinguishing tumor from non-tumor regions?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are differentially expressed at the transition points between tumor progression states?
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Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a specific transcript in tissue?
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Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological pathways are enriched for neighbor-dependent genes?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory Inference
Does denoising improve the spatial clarity of cortical layer marker gene expression? 3b: Does denoising reduce noise and sharpen expression differences across genes compared to raw counts? PAPER 197 (MNiST) 7A: Do spatial clustering results align with known cell type distributions across axolotl brain injury time points? 7B: Where are the injury regions located across tissue slices at each time point? 7C: What cell types populate the 15DPI injury region? 7D: What spatial and transcriptional structure characterizes the 15DPI injury region? 7E: What is the pseudotime trajectory structure within the 15DPI injury region? 7F: Which genes vary systematically along the injury-regeneration pseudotime trajectory? 7G: How do key marker genes change dynamically along the inferred regeneration trajectory? PAPER 198 (tensor decomposition) 3a: How is the spatiotemporal gene expression dataset structured as a tensor for decomposition? 3b: What is the spatial layout of tissue sub-regions across de
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
⭐ Data Taxonomy: Modality: Deconvolved / mapped data Resolution of Observation: Functional tissue unit Condition Dimension: Categorical (cell type) Metadata: Tissue; Biological Annotations Data Components: Spatial Coordinates: Native 2D; Biological Annotations; Derived statistics (estimated cell type proportions) Visualized Elements: Observation; Statistic; Feature Task Taxonomy: Biological Axis: Cellular — Cell identity and state Visualization Taxonomy: Abstraction (justify): Partial — spots shown in native tissue spatial layout; cell type proportion encoded as color per spot; morphological detail not shown but spatial positions preserved Chart type: Spatial cell type proportion map (multi-panel, one per cell type) Communicative / Contextualization (justify): Annotation — cell type labels and color scale shown per panel Comparative Design: Juxtaposition (one spatial map per cell type) Layout (justify): Spatial (physical) — spot positions correspond to actual tissue coordinates Sc
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Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What are the dominant cell-type communication patterns in the human intestine tissue section?
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Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : Histological imageChart Type : Line ChartChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Are cells expressing a specific ligand and its receptor physically co-localized in tissue space?
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Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are most highly expressed within a computationally identified spatial domain, and do they represent biologically meaningful markers for that region?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where is specific pathway activity spatially localized in the tissue?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a disease progression state vary spatially across a tissue section?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does denoising improve the spatial clarity of a gene's expression pattern compared to raw measurements?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology and architecture?
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Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial domains?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Network graphCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are transcriptionally distinct tissue subregions connected or related to one another in terms of gene expression similarity?
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Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are the cell clusters organized across the tissue?
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What proportion of predicted cell–cell interactions are classified as short-range (contact-dependent) versus long-range (secreted signaling)?
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Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial domains in the tissue?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of marker genes and the spatial domains?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which are the spatial domains?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are specific cell populations spatially distributed ?
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Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : ContinuosData Components : Gene Expression MatrixData Components : PseudotimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How does a marker gene expression level change along a differentiation trajectory?
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do specific spatial domains show consistently elevated chromosomal copy number gains compared to other domains across multiple tumor sections?
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Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How are transcriptomically defined cell type clusters?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How do non-cardiomyocyte cell types distribute spatially across developmental stages?
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Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Pixel MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How are functional tissue units distributed spatially across conditions?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoverySpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are differentially expressed across spatial domains within a tissue?Which genes are specifically expressed in each spatial domain of a tumor tissue?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
How does the spatiotemporal expression pattern of a second protein of interest compare in its tissue distribution, cell type specificity, and temporal dynamics?
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Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does denoising improve the spatial clarity of layer-specific marker gene expression?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : CategoricalData Components : Biological AnnotationMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What cell types are present in each spatial tissue?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
In which cell type and neighborhood combinations is a specific protein's estimated expression highest?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which biological pathways are most active in each spatialtissue domain?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Do newly identified marker genes show spatially restricted expression patterns that confirm their association with specific tissue sub-regions?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the relative abundance and distribution of cell types within a specific spatial domain?
View paper
Görtler F. et al. - 2024

Adaptive digital tissue deconvolution

Condition Dimension : N/AData Components : StatisticMetadata : No metadataModality : Sequencing-basedModality : SimulatedResolution of observation : MolecularVisualized Elements : FeatureBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Venn diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designScalability Strategy : Sampling/Filtering
Which gene expression changes are shared or unique across different disease subtypes?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatial domains express marker genes supporting biological identity?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Space-fillingScalability Strategy : Summay/Aggregate
What cell types make up each spatial region?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the spatial domains in the tissue?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of tumor and non-tumor regions in a cancer tissue section as defined by expert annotation?
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Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the expression of marker genes compare with cell types annotation?
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Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue do cells co-express receptor–ligand pairs, suggesting active intercellular communication?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell-cell communication signals are strongest in a specific condition?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are related cell subtypes spatially segregated, and what molecular markers define each?
View paper
Yuan et al., 2020

GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Do spatial expression patterns of a ligand and a non-interacting receptor show less co-localization than a true ligand-receptor pair?
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Yang J. et al. - 2024

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Do layer-specific marker genes show differential expression patterns that align with the spatial domains detected by the method?
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Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatially distinct pathological regions within a tumor tissue section?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes are differentially expressed between distincttumor subregions?
View paper
Fu Y. et al. - 2025

A multi-view graph convolutional network framework based on adaptive adjacency matrix and multi-strategy fusion mechanism for identifying spatial domains

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the distribution of marker gene expression differ across annotated spatial layers in original versus reconstructed data?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do genes cluster based on refined embeddings in reduced dimensional space?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Can computational methods recover the known anatomicallayer structure of a tissue from spatial transcriptomic data?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : MolecularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What is the main biological function associated with the genes that define the discovered module?What is the main biological function associated with the marker genes?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of a spatially defined tissue region?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the spatial distribution of tumor cell proportions?What is the spatial organization of tumor progression states?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
How does pathway activity vary across different spatial microenvironments?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the functionally distinct spatial domains based on gene co-expression?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the expression level or association score of interaction-dependent genes vary across different cell-type pair contexts?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What cell types express specific genes at single-cell resolution?
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do deconvolved cell type proportions recapitulate the known tissue organization of a developing mouse embryo, including rare cell populations?
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the expression patterns and domain specificity of marker genes?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Does the expression of specific molecular markers vary across spatially distinct tissue domains?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Data Components : Clinical dataGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular Niches
Is the abundance of a specific tissue niche type associated with patient survival outcomes?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : No scalability strategy (Item-level)
How do genes within a biological theme interact?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does cellular microenvironment influence gene expression within a cell type?
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Kambhampati S. et al. - 2025

TissueMosaic: Self-supervised learning of tissue representations enables differential spatial transcriptomics across samples

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixMetadata : Experimental : DonorModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes are differentially expressed between cells from spatially enriched young versus old tissue motifs?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
How can spatial and expression relationships be interactively explored?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How does the activity of a gene co-expression module vary across cells in both transcriptional and physical tissue space?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which pairs of cell types are significantly co-localized in spatial proximity within a tissue?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does denoising change the spatial expression patterns of marker genes?
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial organization of cell types in a coronal brain section when assigned by cell segmentation?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can 3D spatial transcriptomics reveal spatially variable genes whose expression patterns are only apparent when multiple tissue sections are analyzed together in three dimensions?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the 3D spatial organization of all cell types in tissue?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Microscopy imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are ligand and receptor expression spatially co-localized?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs mediate communication from niche cells to a specific cell type?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Dot ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are the key markers located in healthy and diseased tissues?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which target genes are shared versus specific between two co-active transcription factor regulons?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do different immune cell types spatially associate with each other?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Are co-expression patterns of ligand-receptor pairs better revealed?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do certain cell types show spatial clustering or co-localization within a tissue section?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Network graphChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Do cell clusters derived from the reconstructed communication graph form coherent low-dimensional representations for the seqFISH+ data?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the tissue regions?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which communication signals are strongest across the entire tissue?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Are there transcriptomic similarity between spatially separated tissue regions that share similar cell identities?
View paper
Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How are transcriptomically defined cell type clusters?How do transcriptomically defined cell type clusters map back to spatial positions in the cerebellum?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Which spatial domains are present in the tissue?
View paper
Hakobyan S. et al. - 2025

Topology-aware pathway analysis of spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesChart Type : HexplotChart Type : Network graphCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Which genes act as molecular bridges connecting activity in one biological pathway to the activation of a neighboring pathway?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial relationships between expression programs?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : Physical
How are spatial transcriptomics spots distributed across tissue regions?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does summarizing spatially identified clusters into higher-level anatomical parcellations reveal known brain organization?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do pathway activities differ between cancer morphotypes?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do domain-specific marker genes show spatially restricted expression patterns that align with the detected tissue domains?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do molecular expression patterns align with anatomical regions?
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does accounting for feature importance scores alter the inferred number of ligand-receptor interactions between cell type pairs?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which are the spatial expression patterns of marker genes?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does cell type spatial organization vary across tissue depth?
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are the cell clusters corresponding to highlighted palette colors spatially located?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial organization of all cell types in tissue?
View paper
Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Modality : scRNA-seqOther : UI / Screenshot
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference anatomical organization of embryonic structures?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial layout of thalamic neuron subtypes on a virtual sagittal section generated from a 3D reconstructed brain volume?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do the cell counts of cells expressing each marker gene differ between healty and diseased tissues?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns for a selected gene?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial distribution of gene expression patterns?What is the spatiala distribution of a spatial domain?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What cell types are present in the tissue?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are different cell types spatially distributed across a tumor tissue section?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Where are specific proteins expressed in different tissue regions?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do different immune cell states show significantly different levels of a functional score?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does cell type abundance vary across identified spatial domains?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : scRNA-seqResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What cell types are present in the reference dataset?
View paper
Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : SimulatedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the distribution of the cell populations?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D Spatial anatomical mapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How are anatomical brain structures spatially distributed across 2D sections and in the whole 3D brain volume?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do cell-cell signaling patterns differ between cell states?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference anatomical annotation used to validate spatial transcriptomics clustering results?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : TimeModality : scRNA-seq
View paper
Budhkar et al., 2024

xSiGra: explainable model for single-cell spatial data elucidation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial distribution of gene importnace scores in a specific cell type in a defined tissue region?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial organization of cell types in diseased tissue?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : DendogramChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Are the predicted spatial assignments of cells to hypothalamic nuclei supported by the expression of known nucleus-specific marker genes?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a specific gene across a tissue section?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the established anatomical region boundaries used as a reference for evaluating spatial transcriptomics results?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a specific transcript in tissue?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How are transcriptionally defined cell populations spatially organized in tissue?What distinct cell populations are present based on transcriptional profiles?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : 3D Spatial anatomical mapChart Type : Spatial gridChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the brain is a specific gene expressed, and how does its expression pattern relate to anatomical boundaries in both 2D sections and 3D space?
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Xu Z. et al. - 2024

STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do the spatial expression patterns of multiple genes evolve across embryonic development, and do different genes show distinct spatiotemporal dynamics?
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Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What neuronal and non-neuronal cell types are present across multiple brain tissue sections?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Is there a correlation in the expression levels of the interacting genes between two cell types?
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are enriched ?
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Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What cell types are present in a breast cancer sample and how are they transcriptionally clustered?
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Shi M. et al. - 2024

STPDA: Leveraging spatial-temporal patterns for downstream analysis in spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How does the expression patern of interacting ligand-receptor gene pairs look?
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Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How spatially close are different cell types to a specific reference cell population in a tissue?
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Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixModality : SimulatedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
How similar are the gene signature across the different clusters?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes change in expression most dynamically along a transcriptional time axis inferred from velocity?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What cell types are present in each spatial tissue?
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Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/Filtering
What is the inferred hierarchical progression pathway between different tumor subpopulations?
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Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are individual molecular signals spatially distributed across conditions?
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Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can spatially coherent regions of interest be identified within a heterogeneous tumor tissue?
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Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue are chromosomal copy number losses spatially distributed, and do they align with tumor versus non-tumor regions?
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Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How are cell types and spatial domains co-localized?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What confounding variables exist in cellular neighborhoods?
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Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology?
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Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spatial domains identified from cell type proportions correspond to the spatial distribution of their constituent cell types?
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Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Metadata : Experimental : SampleGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular Niches
Is the abundance of a specific tissue niche type associated with patient survival outcomes?
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Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : 3D ScatterplotChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What are the spatial domains in 3D?
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Qing J. et al. - 2025

SCNT: an R package for data analysis and visualization of single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell clusters spatially organized across the entire tissue section?
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Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : No scalability strategy (Item-level)
How does parameter choice affect method performance?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How are atrial and ventricular cardiomyocytes spatially segregated in the three-dimensional developing heart?
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Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingScalability Strategy : Summay/Aggregate
Which genes are involved recurrently in multiple modules?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What are the characteristic cellular compositions of spatiallydefined multicellular niches in a tissue?
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do the spatial domains identified by the tool compare with the manual annotation?
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Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of domain-specific marker genes?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Does spatial gene expression imputation faithfully recover expression patterns in unmeasured tissue regions?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are MHC1 antigen presentation signals distributed spatially?
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Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
How are enriched gene sets related to each other?
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Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
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Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do computationally identified cell-type-associated signals partition spatially across a tissue section?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
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Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns of domain-specific signatures?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes serve as known markers for specific tissue layers or regions?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What genes are expressed in cells based on their neighboring cell types?
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Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which tumor genes are upregulated or downregulated in regions with high immune cell abundance?
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Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do specific genes show spatially graded expression patterns within a single cell type, and can these be recovered from noisy single-bead measurements?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which biological pathways are enriched in a spatially defined tissue region?
View paper
Niu J. et al. - 2025

SpatialCVGAE: Consensus Clustering Improves Spatial Domain Identification of Spatial Transcriptomics Using VGAE

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotChart Type : Violin plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do gene expression levels differ between two identifiedspatial tissue domains?
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Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : DendogramChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedScalability Strategy : No scalability strategy (Item-level)
Which are the patterns between the correlation of genes?Which genes are expressed across the tissue?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial organization of tissue layers in the sample?
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Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Anatomical & Spatial Domain DiscoverySpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How do different clusters partition a tissue into regions?What are the characteristic gene expression landscapes of transcriptionally distinct spot clusters?
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Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the top marker genes between spatial domains?
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Truong L. et al. - 2025

OmnibusX: A unified platform for accessible multi-omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : No abstractionAbstraction : PartialChart Type : Dimensionality reductionChart Type : Flourescence tissue imageChart Type : Histological imageChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Other : UI / Screenshot
What are the cell clusters of teh dataset, and how are they located in the tissue?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are chemoattractant signals distributed spatially in tissue environments?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Sequencing-basedModality : SimulatedVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How does the spatiotemporal latent expression pattern of a second protein differ from or complement that of a first protein across the tissue?
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Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Which are the cell types presents in tissue?
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Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does cell type spatial organization vary across tissue depth?Where are specific genes expressed within the tissue architecture?
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Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of specific genes across tumor regions?
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Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial organization of cell types in tissue?
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Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
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Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Flourescence tissue imageChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are multiple marker genes co-distributed at ultra-high spatial resolution within a tissue, and do their expression domains overlap or segregate?
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Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do computationally identified spatial domains correspond to known hippocampal subfields?
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Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What biological processes are transcriptomically enriched ?
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Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do major brain regions map spatially across a tissue section?
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Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells cluster in gene expression space, and how many distinct cell types can be identified?
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Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do gene pairs show higher colocalization scores than self-pairs, and does this differ between nuclear and cytoplasmic compartments?
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Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : No scalability strategy (Item-level)
What is the three-dimensional shape and location of specific brain region clusters when reconstructed from serial sections?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
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Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does gene expression vary spatially across tissue sections before and after alignment?
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in tissue do ligand and receptor expressing cells co-localize to enable cell-cell communication?
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Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are different cell types spatially distributed across a tumor tissue section?
View paper
Shi M. et al. - 2024

STPDA: Leveraging spatial-temporal patterns for downstream analysis in spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How does the raw expression pattern of non-interacting gene pairs look?
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Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what are the spatial patterns of variation in the gene expression data?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell type composition at each spatial location within a tumor tissue section?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent cell communities are discovered in the tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
Which cell types are present?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the level of expression of specific genes across different cell subtypes?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How specifically are marker genes expressed in their target domain compared to all other domains?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : PseudotimeModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotChart Type : Vector field plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
In which direction are cells transcriptionally changing within identified tissue domains, and is there a directional differentiation gradient?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do predicted cell-cell signaling interactions differ when spatial constraints are not applied?What are the predicted cell-cell signaling interactions through a specific pathway within a spatial community?
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Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial domains emerge from clustering based on cell type proportions in large-scale olfactory bulb data?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cells cluster when spatial interaction information is incorporated into their representation?Where are different spatially informed cell types located within the tissue?Where are the different cell types located within the tissue?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the number of a given cell type relate to its degree of infiltration into a neighboring cell population across patients?
View paper
Keller et al., 2025

Vitessce: integrative visualization of multimodal and spatially resolved single-cell data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : No abstractionChart Type : ScatterplotChart Type : Violin plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/AggregateOther : UI / Screenshot
Where are specific RNA molecules located within and between cells in tissue?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Where in tissue do specific cell-cell communication events occur?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
Where in the 3D tissue is a specific gene expressed?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does cell type composition vary across spatially defined tissue domains?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularAbstraction : CompleteChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the in situ hybridization expression pattern of a candidate spatially variable gene align with the tissue's known anatomical structure?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : CircularScalability Strategy : Summay/Aggregate
What is the composition of cell types within a selected tissue region?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does spatial proximity between cells differ based on cell type and community membership?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What cell types are present in a tumor microenvironment and how are they transcriptionally related?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are MHC2 antigen presentation signals distributed spatially?
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Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : Line ChartChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Do tumor-specific spatially variable genes have prognostic value in independent patient cohorts?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How do gene correlations vary across tumors for a specific cluster of gene pairs?
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Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial expression gradients relative to tumor boundaries?
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Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does improving spatial resolution via computational windowing reveal finer spatial organization of cell types compared to coarser binning?
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Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What biological functions are associated with expression programs?
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Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue organization?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
What gene signatures characterize different tumor spatial neighborhoods?
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Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : Ordered : ContinuosData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What is the developmental progression of cells?
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Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteAbstraction : PartialChart Type : HexplotChart Type : Violin plotCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Are spots at tumor-adjacent domain boundaries transcriptomically enriched compared to other boundary spots?
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Andersson A. et al. - 2024

Points2Regions: Fast, interactive clustering of imaging-based spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : CellularBiological : MolecularAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do samples from different donors or batches cluster separately?
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Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do the cell type annotation align with their location in the original tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What spatial clusters are present?
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Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Do immune intensities differ between glomerular and non-glomerular regions experimentally?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue regions spatially distributed across a cancer tissue section as annotated by pathologists?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Space-fillingScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which biological pathways are differentially active between spatially distinct tumor regions, and are these patterns consistent across patients?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatial domains express marker genes supporting biological identity?
View paper
Xu et al., 2022

Spatial Transcriptomics Dimensionality Reduction using Wavelet Bases

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the gene expression patterns?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the spatial co-localization of cell types predict intercellular signaling patterns within a tissue niche?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do image-derived features — such as nuclei density and marker intensity — vary spatially across a tissue section when mapped to spatial transcriptomics capture locations?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the cellular composition differ across spatially distinct regions of interest within a tumor?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is cell cycle activity spatially distributed in tissue?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does the average abundance of different cell types change over time following a therapeutic intervention?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : No scalability strategy (Item-level)
What biological pathways differ between expression programs?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Does the effect of spatial proximity to tumor cells on immune cell functional state differ across immune cell subtypes?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of known organ-specific marker genes in a developing embryo?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do standard dimensionality reduction methods reveal the developmental trajectories and cell type diversity of brain organoids?
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Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How can the local spatial structure of a multicellular niche be examined at different scales within a tissue?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
How do genes clusters seprate in reduced dimensionality?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedVisualized Elements : StatisticBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of each cell type's spatial neighborhood?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the molecular spatial domains across multiple tissue samples?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does denoising affect the spatial expression patterns of region-specific genes?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the morphological structure of the tissue sample?
View paper
Li W. et al. - 2024

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially predicted kidney cell type proportions co-localize with the expression of their known marker genes?What are the pattern expression of the known marker genes?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What does the tissue morphology look like?
View paper
Lyu Y. et al. - 2024

Regional analysis to delineate intrasample heterogeneity with RegionalST

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Space-fillingScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which biological pathways are differentially enriched across spatially defined regions of a tumor?
View paper
Mohanty C. et al. - 2024

SpatialView: an interactive web application for visualization of multiple samples in spatial transcriptomics experiments

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : MolecularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteAbstraction : No abstractionAbstraction : PartialChart Type : HeatmapChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/FilteringOther : UI / Screenshot
How are transcriptional clusters spatially organized across a tissue section in the context of tissue morphology?What are the gene expression characteristics of a selected spatial spot and what does the surrounding tissue look like?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where do distinct cell populations localize in a tumor and what genes mark each domain?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How well do computationally derived de novo clusters correspond to previously published cell type annotations?
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Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/Filtering
Which genes are co-expressed with a specific ligand-receptor pair?
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Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell types?
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Avesani S. et al. - 2022

Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the morphological characteristics of different tissue types?
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Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does the abundance and morphology of a specific cell type change across different tissue regions and time points following a perturbation?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How do the cell type annotation align with their location in the original tissue?
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Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Violin plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes differ in expression between spatial domains?
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Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial tissue domains?
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Yang J. et al. - 2024

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where are erythrocytes located based on marker gene expression?
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Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of different spatial communities?
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Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the three-dimensional spatial organization of cell types or brain regions in the mouse brain as measured by volumetric in situ sequencing?
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Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the expression of the SVG genes?
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Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does the spatiotemporal expression pattern of a second protein of interest compare in its tissue distribution, cell type specificity, and temporal dynamics?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How predictive is the neighborhood cell composition for determining the central cell's identity across all detected cell types?
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Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Spatial gridCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do transcriptomically defined cell clusters correspond to morphologically identifiable cell types in matched histological images?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapChart Type : Network graphCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes are co-regulated across cell types and disease stages during colitis progression?
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Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the detected spatial domains?
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Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial expression patterns are characteristic of genes exclusively identified as spatially variable?
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Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : Pie ChartChart Type : Scatter pieCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spot of different slices relate between them?
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Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How close are different spatial domains to each other?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the expression of the SVG genes?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the organization of the cells?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are annotated cell types spatially distributed across a cortical tissue section in a MERFISH dataset?
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Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : SimulatedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does molecular diffusion affect cell type identification accuracy?
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Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which communication signals are strongest across the entire tissue?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Do the molecular factor of a cell type co-vary with the molecular factors of specific neihboring cell types? Are any potential co-regulated signaling loopd?
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Zhang K. et al. - 2022

Identification of spatially variable genes with graph cuts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does tissue domain reconstruction quality vary depending on which method's SV genes are used?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the gene expression level and cell prevalence varies between healthy and diseased states?
View paper
Shi M. et al. - 2024

STPDA: Leveraging spatial-temporal patterns for downstream analysis in spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
How does the raw expression pattern of non-interacting gene pairs look
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Functional Enrichment & Pathway ActivitySpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : CompleteAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do two pathway activities relate to each other across observations?Where are spots with specific pathway activity profiles located in tissue?
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Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference laminar organization of a tissue as annotated from imaging?
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Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/Filtering
Which transcripts show significant spatial co-expression relationships?
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Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are the spatial boundaries of biologically distinct tissue regions defined for use as a covariate in spatial DE analysis?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : SimulatedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Bar plotChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How many cells of each rare cell type are detected across iterations?
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Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What disease associations characterize spatial domains within a tissue sample?
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Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Network graphComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
Can groups of genes with similar relationship patterns be identified?Which are the patterns between the correlation of genes?
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Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Functional validation between the interacting factors
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Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do discrete biological stages map onto spatial locations within a tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct cell states distributed spatially within a tissue compared to their organization in transcriptional embedding space?
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Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
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Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific cell types predominantly located?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue do cells at different stages of a developmental trajectory reside?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are annotated cell types spatially distributed across a tissue section in an imaging-based spatial transcriptomics dataset?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Word CloudCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Summay/Aggregate
What biological themes are represented by gene set clusters?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do spatial frequency filtering operations alter the visual representation of transcriptomic patterns in tissue?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific signals localized within spatial structures?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the spatial domains present?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do tumor cells near immune cells show higher expression of a set of functionally related genes?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How are cell types distributed across spatial domains?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedModality : scRNA-seqResolution of observation : Functional tissue unitVisualized Elements : Statistic
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial gridCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are annotated cell populations distributed across tissue space?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures in tumor tissue?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do feature patterns cluster across categories?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the relative abundance of each cell type in a tumor microenvironment?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different cell types spatially distributed across a tissue section?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : StatisticMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What is the spatial relationship between different cell types?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show spatially variable expression patterns in a tissue section?
View paper
Allen C. et al. - 2023

A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the pairwise correlation patterns among a set of genes?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
What is the three-dimensional spatial organization of the major compartments of the Drosophila digestive tract?
View paper
Zhao et al., 2024

A Part-to-Whole Circular Cell Explorer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial organization of cell clusters and gene expression patterns?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes serve as markers for distinguishing identified cell populations?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do pseudospot-level spatial clusters organize across a tissue section and in low-dimensional embedding space?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
Does the method successfully mix gene expression profiles from multiple biological batches in the low-dimensional space?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue organization?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Space-fillingScalability Strategy : Summay/Aggregate
How does the cellular composition vary across spatial tissuedomains?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do computationally detected spatial domains correspond to transcriptionally distinct cell populations?What molecular markers are specifically expressed in each spatially defined cell-type domain?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are tumor and non-tumor regions located within atissue section, and how is the tumor boundary spatially defined?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the relationship between cell types and spatial domains?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does a spatially mixed tumor microenvironment look like, where one cell type infiltrates a neighboring population?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial organization of cell types in tissue?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Does clustering based on deconvolved cell type proportions produce different spatial domains compared to clustering based on raw gene expression?
View paper
Andersson A. et al. - 2024

Points2Regions: Fast, interactive clustering of imaging-based spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What are the cell clusters present in the tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which are the cancer associated regions?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes drive each contrastive component?
View paper
Li et al., 2023

Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Space-fillingScalability Strategy : Summay/Aggregate
What are the proportions of the neighbors of each spatial domain?
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes and molecular functions are uniquely enriched in each ductal cell subtype, providing functional insight into their roles in cancer?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
How spatially enriched are different astrocyte subtypes in proximity to each other?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct tissue regions spatially organized within a tumor section as identified by expert pathologists?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatial paths does tumor progression follow within the tissue section?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a pathway?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : Biological statusMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What spatial and transcriptional structure characterizes the 15DPI injury region?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatial gene expression patterns do contrastive components capture across brain regions?
View paper
Frost H.R. - 2025

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How can multi-gene expression patterns be encoded simultaneously into a single color-based spatial representation?
View paper
Bafna M. et al. - 2023

CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedModality : SimulatedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial structure of the cell interaction network ?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How frequently are each pair of cell types spatially co-localized in a tissue, and do these patterns match known anatomical organization?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do cells with similar high-dimensional transcriptomic profiles form spatially coherent neighborhoods that correspond to known anatomical regions?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are tumor and stromal cell populations spatially organized within a breast cancer tissue?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a cell-type marker gene across a tissue section?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are consistently expressed across tumor regions from different sections of the same patient, and which are unique to a specific sample — and how does this vary spatially?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are tumor cell types spatially organized within a tumor section?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Does total gene expression density reveal tissue structure ?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : Linear
What are the expression profiles of the differentially co-expressed gene modules that characterize the different stages of cancer evolution?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : Histological imageChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific cell types enriched within tissue anatomy?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : 3D Spatial anatomical mapChart Type : Spatial gridChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
How is a gene's expression distributed across fine-grained anatomical subregions of a specific brain area?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

General Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the cell's organization in the tissue?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are most highly expressed within a computationally identified spatial domain, and do they represent biologically meaningful markers for that region?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Do the module gene pairs exhibit significantly higher colocalization propensity compared to random gene pairs and is this phenomenon specific to the module cells?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Sampling/Filtering
Which cell types are present?which genes are expressed? which are marker genes?
View paper
Pardo B. et al. - 2022

spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do transcriptionally defined clusters relate to tissue morphology when visualized side by side on spatial transcriptomics data?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Sampling/Filtering
What is the inferred intracellular signaling pathway from a receptor to downstream transcriptional regulators?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Half violin plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How are marker genes expressed across anatomical layers?How does denoising improve layer-specific marker gene expression?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Does spatial smoothing clarify the underlying continuous expression domains of co-expression modules compared to unsmoothed spot-level maps?What are the average spatial expression patterns for each co-expression module at the native measurement resolution?Which individual genes best represent the spatial expression pattern of each co-expression module in the olfactory bulb?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are distinct tissue domains located within a sample?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What does the tissue look like at the histological level, and where are the major anatomical features located?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are differentially expressed between two identified spatial clusters, and how do expression levels and prevalence differ?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do tissue spot clusters organize in low-dimensional embedding space, and do they reflect known anatomical distinctions?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What molecular pathways define different cancer domain types within a tumor tissue?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How does a principal component vary across cells?What cell types are present?Where is a marker gene expressed?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the spatial distances between different tissue sections in 3D?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the cell types present in the tissue?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
How does cellular organization differ between tissue types?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cell types and their layer-of-origin distribute in a lowdimensional transcriptomic embedding, and do they form distinct clusters?
View paper
Leng J. et al. - 2025

Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotChart Type : Violin plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes differ in expression between spatial domains?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what are the spatial patterns of variation in the gene expression data?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What cell types are present in a fraction of tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the characteristics of the background (normal) and target (diseased) tissue samples?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How do overall cell-cell communication intensities vary across all cell-type pairs in a tissue?
View paper
Wang B. et al. - 2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do tissue spatial domains have distinct gene expression signatures for known marker genes?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which genes show the most characteristic spatial distribution for each subcellular localization pattern within a cell?
View paper
Gong Y. et al. - 2025

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the distribution of marker genes in the tissue (in tumor)?
View paper
Long et al., 2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference tissue domain organization at a later developmental stage?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : No abstractionAbstraction : PartialChart Type : HexplotChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Where in the tissue do cells simultaneously express both a receptor and its ligand, indicating potential sites of intercellular signaling?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which gene pairs show statistically significant spatial association?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What genes are specifically upregulated in each cell type within a tumor?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
which pair of cell types are found in each other's spatial neighborhoods?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
How do cell types interact, and which signaling pathways mediate those interactions?
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Shi W. et al. - 2025

Image-enhanced Multi-Modal Contrastive Transformer for subcellular spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
What are the likely developmental or transitional relationships between cell clusters in a tumor sample?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How many spatially distinct expression domains can be identified in tumor tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : Latent
How do genes cluster based on their expression patterns in reduced dimensional space?
View paper
Chen N. et al. - 2024

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : Tissue unit/StructureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the marker genes for a spatial domain?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Alluvial plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs mediate communication between neuroblasts and neural stem cells, and which are unique to the proposed method?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How can multiple tissue sections be co-registered in a common spatial framework for integrative analysis?How does multiple tissue slices can be co-registered in a common spatial framework?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression of selected genes?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue morphology?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological pathways are enriched among the spatially variable genes uniquely identified by 3D transcriptomics in a disease tissue?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
How do cells from different cortical layers cluster in transcriptional space, and do layer-defined groups align with known cell type identities?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns for a selected gene?
View paper
Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially distributed within a tissue at cellular resolution using a regular grid-based spatial transcriptomics approach?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What disease associations characterize molecular spatial domains?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsModality : Sequencing-basedResolution of observation : MolecularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What is the spatial expression pattern of marker genes in tissue?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell populations organized across different tissue types and disease states?Where are specific genes expressed within the tissue architecture?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatiotemporal expression pattern of a second protein of interest compare in its tissue distribution, cell type specificity, and temporal dynamics?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationVisualized Elements : RelationshipVisualized Elements : Tissue unit/StructureBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do cell types and their developmental pseudotime scores distribute spatially across brain tissue at different developmental stages?
View paper
Long et al., 2024

Deciphering spatial domains from spatial multi-omics with SpatialGlue

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the anatomical structures in the tissue?
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : HexplotChart Type : Vector field plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
In which spatial direction do cells progress along a developmental trajectory in a tumor?
View paper
Keller et al., 2025

Vitessce: integrative visualization of multimodal and spatially resolved single-cell data

Condition Dimension : N/AData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Imaging-basedModality : Spatial proteomicsVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : 3D ScatterplotChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/FilteringOther : UI / Screenshot
How do observations cluster based on protein expression profiles?What is the expression pattern of molecular features across observations?What is the three-dimensional spatial distribution of molecular species in tissue?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in identified gene signatures?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the characteristics of spatial domains?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How are cell types distributed across histological domains?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial expression pattern of a highly spatially variable gene across a tissue section?
View paper
Ke J. et al. - 2025

High-resolution mapping of single cells in spatial context

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Through which signaling pathways does one cell type predominantly communicate with another, and which specific ligand-receptor pairs drive that communication?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Co-expression & Co-localized ModulesSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : No abstractionChart Type : HeatmapChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do spatial gene expression modules differ between conditions?Where are specific cell types spatially located in tissue and how does this differ between conditions?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What genes are differentially expressed across histological domains?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the spatial distribution of neurons look like in a tissue section, as revealed by fluorescent staining?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatial domains does the method identify in embryonic heart tissue, and are they anatomically coherent across sections?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes are differentially expressed across developmental stages in a cell-type-specific manner?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
Do individual genes show spatially coherent expression patterns consistent with known biology?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are distinct cell types spatially organized within a developing tissue when mapped from single-cell data?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell types across the tissue?
View paper
Qing J. et al. - 2025

SCNT: an R package for data analysis and visualization of single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How are cell clusters spatially organized within a tissue sub-region at high resolution?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How does cell differentiation state, as captured by pseudotime, map onto the physical spatial organization of the tissue?
View paper
Pardo B. et al. - 2022

spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : BoxplotChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the gene expression patterns?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Are cell-type spatial domains consistent across multiple tissue sections from the same region?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell's organization in the tissue?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Network graphChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where is a specific multi-hop communication pathway spatially localized?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes best distinguish each cell type identified by a spatial clustering method?
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Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell's organization in the tissue?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do certain cell types show spatial clustering or co-localization within a tissue section?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Co-expression & Co-localized ModulesSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteAbstraction : PartialChart Type : Dot ChartChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
How do meta-programs correlate with metagene expression across tumor regions?What are the spatial patterns of cellular meta-programs across tumor regions?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes and cellular components are enriched among spatially variable genes?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : True 3DMetadata : Experimental : TissueResolution of observation : Functional tissue unitVisualized Elements : Tissue unit/StructureBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : 3D mapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
Which cell types form the spatial niche around a specific cell population within a tissue?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Radial network plotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : Force-directedScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which biological pathways are enriched among differentiallyexpressed genes, and how do these genes interact?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : Line ChartChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesComparative Design : SuperpositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Sampling/Filtering
How does cell type spatial organization differ between healthy and disease conditions?How does cellular co-occurrence change between conditions?Where are specific cell types spatially located in tissue and how does this differ between conditions?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : TimeMetadata : No metadataModality : Sequencing-basedModality : SimulatedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Do distinct cell states along a biological transition separate into distinguishable clusters in low-dimensional embedding space?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of cell-type or region compositions across a tissue section?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Force-directedScalability Strategy : No scalability strategy (Item-level)
Which genes are co-expressed in functional modules?
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Boundary & Interface DynamicsSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are spatial interaction zones located relative to cortical layer boundaries?Where are the spatially defined interaction zones located within the tissue section?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the ground truth spatial organization ?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spatially resolved transcriptomic clusters correspond to anatomically distinct regions in a tissue section?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticModality : Imaging-basedResolution of observation : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes exhibist the highest positive or negative correlation in key cell types?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is tumor subclone diversity spatially distributed across anatomical structures in a tissue section?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the relative spatial distances between cell types?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the marker gene expression patterns that characterize cell types within a spatial community?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does ligand-receptor coexpression for a specific pair compare to all pairs?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Which immune cell states preferentially co-localize in the spatial tumor microenvironment?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/Filtering
Do genes in a specific pathway show a coordinated spatial gradient of expression from the center to the periphery of a tumor?
View paper
Marco-Salas S. et al. - 2021

Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can a spatial gradient be defined and quantified across a tissue section to enable ordered positional analysis?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
Which brain region clusters are most spatially co-localized with the Hippocampus at different distance scales?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Data Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially distinct gene co-expression patterns are in lung cancer tissue?
View paper
Kamel M. et al. - 2024

SpatialOne: end-to-end analysis of visium data at scale

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do the spatial locations of a specific cell type co-localize with high expression of their marker gene?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes show correlated expression in cellular neighborhoods?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spatial domains identified by deconvolution correspond to the spatial abundance of their defining cell types and the expression of their marker genes?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial distribution of annotated cortical layers in the tissue, used as reference for analysis?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : StatisticModality : SimulatedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellullar composition of spatially defined tissue regions?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the community structure of the tissue?
View paper
Guo B. et al. - 2023

escheR: unified multi-dimensional visualizations with Gestalt principles

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How can cell-type identity and gene expression be simultaneously encoded in an embedding visualization without visual ambiguity?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
Which cell types are present?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do cell types identified in gene expression space form spatially coherent regions in the tissue?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Sampling/Filtering
What is the three-dimensional distribution of salivary gland tissue across the reconstructed embryo volume?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seqVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What distinct immune cell states are present in a tissue as revealed by single-cell transcriptomics?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Force-directedScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which cell types communicate with each other through specific ligand-receptor pairs?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotChart Type : Sankey diagramCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the expression of a specific transcription factor vary across cell types and developmental time points?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
In which cell types or domains is a set of marker genes expressed, and at what level?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticModality : Imaging-basedResolution of observation : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes exhibist the highest positive or negative correlation in key cell types?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
Which ligand-receptor pairs drive the most widespread predicted cell–cell interactions across a tissue?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What tissue architecture serves as spatial ground truth?
View paper
Zhang D. et al. - 2024

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are enriched ?
View paper
Liang Q. et al. - 2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial expression gradients in tissue?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What spatially distinct gene co-expression patterns are in lung cancer tissue?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
identify cells with shared functional patterns
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do annotated tissue layers correspond to spatial positions in a brain tissue section?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cellular composition of the tissue?
View paper
Guo L. et al. - 2023

VT3D: a visualization toolbox for 3D transcriptomic data

Condition Dimension : Ordered : DiscreteData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does spatial gene expression and tissue organization change during developmental stages in 3D?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : CellularBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How does the distance between cell and the fraction of close pairs of cells for each marker vary across healthy and diseased states?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What anatomical or functional brain regions are transcriptomically enriched in a computationally identified cluster compared to another?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Do different tumor regions identified by transcriptomics correspond to histologically distinct morphologies visible in the tissue?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which biological pathways are enriched in a spatially defined tissue region?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell organization of the different cell types?
View paper
Li F. et al. - 2025

SPathDB: A comprehensive database of spatial pathway activity atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of a pathway?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do cancer spots sub-partition spatially in prostate cancer tissue?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How are cells related based on ther transcriptional profiles?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Were are the cell clusters located?
View paper
Wang K. et al. - 2023

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Other : Database
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : PartialChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do spatially proximal cells receive stronger signals from a ligand-expressing source cell population than distant cells?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Dimensionality reductionChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What are the lineage relationships and transition paths between cell types in a developing tissue?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What microenvironments exist within the tissue and where are they located?
View paper
Guo L. et al. - 2023

VT3D: a visualization toolbox for 3D transcriptomic data

Condition Dimension : N/AData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does cardiac tissue organization and gene expression change spatially during heart development in 3D?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where are specific marker genes expressed in 3D reconstructed tissue?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How domain-specific are the identified genes?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedModality : SimulatedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
Which proteins show co-regulated spatiotemporal latent effects, as measured by pairwise correlation?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What genes are differentially expressed across spatial neighborhoods?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalCondition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Which cell types are present?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Where in the tissue are specific cell types predominantly located?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are enriched ?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : Tissue unit/StructureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What genes most strongly define the identity of a specific tissue region or cell population?
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is the tissue section partitioned into fields of view for cellular-scale color difference evaluation?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
Where is the tumor located in the tissue?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are differentially expressed across spatial tissue clusters, and do they show cluster-specific marker gene patterns?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the distinct spatial tissue regions in a tumor sample?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does cell density vary across tissue regions and over time following a perturbation?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Data Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : ScatterplotComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells cluster according the transcripts?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are most highly expressed within a computationally identified spatial domain, and do they represent biologically meaningful markers for that region?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticModality : Imaging-basedResolution of observation : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes exhibist the highest positive or negative correlation in key cell types?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteAbstraction : PartialChart Type : Network graphChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Which genes are spatially co-expressed with KRT17 in the tumor microenvironment?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the tissue organization?
View paper
Xu H. et al. - 2023

SPACEL: deep learning-based characterization of spatial transcriptome architectures

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue are chromosomal copy number gains spatially distributed, and do they correlate with the tumor domain boundary?
View paper
Long et al., 2024

Deciphering spatial domains from spatial multi-omics with SpatialGlue

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedModality : Spatial proteomicsResolution of observation : Sub-cellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the protein markers for each spatial domain?
View paper
Islam M.T. and Xing L. - 2023

Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
what are the spatial patterns of variation in the gene expression data?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Where are gene co-expression modules active within tissue structure?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which spatial tissue domains are preferentially adjacent to oneanother in a tissue section?
View paper
Salamon J. et al. - 2018

Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : CircularLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
How do spatial co-expression relationships vary across tissue regions?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do IC weight compositions vary across spot clusters in low-dimensional embedding space?
View paper
Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the cellular composition of a tissue vary across spatially defined domains?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue morphology of the sample look like ?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial domains in this tissue?
View paper
Xie A. et al. - 2025

gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the full spatial landscape of all deconvolved cell type proportions across the tumor tissue section?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does the neighbor-dependent gene show spatially coherent elevated expression at heterotypic contact sites?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes show spatial co-expression patterns with specific target genes?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : No comparative designLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
where is the cellular composition of different spatial microenvironments and how are cells arranged within them?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : MolecularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do the overall intensity distributions of all measured markers change at the single-cell level between healthy and diseased tonsils?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial expression patterns of top-ranked spatially variable genes identified by a statistical model?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Biological statusMetadata : Experimental : DonorModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell-cell communication signals are strongest in a specific condition?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are enriched ?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are specifically associated with distinct cell fate trajectories?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the 3D spatial distribution of cell types in tissue?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What are the relative spatial distances between cell types in 3D reconstructed tissue?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatially coherent cell communities exist within the tumor microenvironment?
View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : HexplotChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do the local microenvironment signaling profiles of spatial transcriptomic spots cluster in low-dimensional space?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How can a specific spatial region of interest within a tissue be identified and visually delineated from the rest?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does a disease condition alter the spatial distribution of cell-type-specific gene expression in a tissue?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Cell-Type & Cell-State MappingSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the selected key cell types (those highlighted spatially in (b)) appear in the low-dimensional gene expression space?How do the selected key genes are expressed across the different cell's clusters?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : Experimental : Treatment groupModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Gradient color plotChart Type : Pixel MapChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
How are functional tissue units distributed spatially across conditions?What are the average spatial patterns of cell-cell interactions across multiple functional tissue units?What are the spatial locations of functional tissue units?What are the spatial patterns of cell-cell interactions within functional tissue units?Where are specific cell types spatially located within functional tissue units?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do cancer-associated spots sub-partition spatially into distinct subpopulations?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cellular neighborhoods spatially distributed across time?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do representative genes show spatially coherent expression consistent with their component?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where is a specific marker gene expressed in tissue?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-based: Deconvolved dataResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are different cell types spatially distributed across tissue locations?
View paper
Velazquez D. and Fan J. - 2025

scatterbar: an R package for visualizing proportional data across spatially resolved coordinates

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Pie ChartChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Space-fillingLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
What is the spatial distribution of cell type compositions across tissue?
View paper
Peng L. et al. - 2023

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What gene expression signatures distinguish spatially defined clusters in breast cancer tissue?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which genes are expressed across the tissue?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Histological imageChart Type : Schematic anatomical diagramCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do the co-expression clusters identified in the Xenium dataset align with known mouse brain anatomical structures?
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
Where in the tissue are specific genes expressed, and does their spatial pattern match expected anatomical layers?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do domain-specific SVGs show spatially coherent expression patterns consistent with their assigned domain?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the marker gene expression patterns that characterize cell types within a spatial community?
View paper
Fang Z. et al. - 2024

stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : Dimensionality reductionChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What developmental or spatial progression trajectory connects the identified clusters, and is this consistent with known anatomical organization?
View paper
Zhang T. et al. - 2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do marker genes for a given cell type show spatially concordant expression patterns with the predicted locations of that cell type?
View paper
Hakobyan S. et al. - 2025

Topology-aware pathway analysis of spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially resolved pathway activity scores agree in their tissue-level spatial distribution?
View paper
Guo Y. et al. - 2024

BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the cellular composition of a tissue vary across spatially defined domains?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which functional cellular compartments are significantly enriched among genes assigned to each subcellular RNA localization pattern?
View paper
Cao R. et al. - 2023

SMDB: A Spatial Multimodal Data Browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are molecularly defined clusters spatially organized across anatomical regions?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How does the spatial distribution of specific cardiac cell types change across developmental stages of the embryonic heart?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cells organized into anatomical layers within the tissue?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which gene best characterizes the local transcriptomic neighborhood?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the spatial cell type distributions across the tissue?
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearLayout : Space-fillingScalability Strategy : Summay/Aggregate
What is the cell type composition of each spatial domain in alayered tissue structure?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What does the spatial arrangement of cells look like withindifferent types of multicellular tissue niches?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Immunofluorescence imageCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What is the spatial distribution of a specific marker in tissue as measured by immunofluorescence?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Do co-expression gene modules display spatially distinct patterns within a specific cell population?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are different cell types located within the tumor tissue?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Other : UI / Screenshot
What are cell types present in the tisssue and how they correlate with the transcriptional landscapes?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : HexplotChart Type : Histological imageChart Type : Line ChartCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Do individual genes within a cluster show the expected spatialexpression pattern along a tissue axis, and how well does the model capture it?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Do certain neighboring cell types have a significant effect on the presence of specific central cell types within their niches?How predictive is the neighborhood cell composition for determining the central cell's identity across all detected cell types?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What defines the local neighborhood environment of individual cells?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do biological pathway activities differ between distinct tumor cell subclones?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do genes cluster into co-associated modules?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are most specifically expressed in each cell cluster and how statistically significant is their differential expression?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Data Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : SimulatedResolution of observation : CellularVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the characteristic spatial patterns used to simulate Spatially Variable Genes (SVGs) for the evaluation?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : TimeMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Sankey diagramCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How does the abundance and composition of cell types change across developmental time points?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What is the expression level of these?Which ligand-receptor pairs are strongly correlated with the specific molecular factors of the central and niche cells?
View paper
Zhou Q. et al. - 2025

Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
How do pathway activities differ between cancer morphotypes?
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of specific cell type genes?What are the spatial expression patterns of specific genes across tumor regions?What is the spatial distribution of specific cell types?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are different features distributed spatially across a tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the tissue organization?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are immune cell states spatially distributed relative to tumor cell density in a tissue section?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : True 3DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalLayout : Spatial : Physical 3DScalability Strategy : No scalability strategy (Item-level)
How are specific cell types distributed in three-dimensional space?
View paper
Preibisch S. et al. - 2025

Scalable image-based visualization and alignment of spatial transcriptomics datasets

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of multiple genes across consecutive tissue sections in their original orientation?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are enriched in identified gene signatures?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Targeted Feature ExpressionSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
What is the expression level of these?Which ligand-receptor pairs are strongly correlated with the specific molecular factors of the central and niche cells?
View paper
Xi J. et al. - 2022

STtools: A comprehensive software pipeline for ultra-high-resolution spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the coarse spatial organization of cell types in the cerebellum when data is binned at the multi-cellular scale?
View paper
Niu J. et al. - 2025

SpatialCVGAE: Consensus Clustering Improves Spatial Domain Identification of Spatial Transcriptomics Using VGAE

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes are differentially expressed across spatialdomains, and do domains have distinct transcriptional signatures?
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What proportion of predicted cell–cell interactions are classified as short-range (contact-dependent) versus long-range (secreted signaling)?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : ProteomicsResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
What protein expression patterns define different cell clusters?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
What are the biological processes that characterize the overall cell type identity of the cells belonging to the discovered module?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : ObservationBiological : TissueAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
What major cell types are present in the hypothalamus and how are they distributed in transcriptional embedding space?
View paper
Chitra U. et al. - 2025

GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : PartialChart Type : Spatial Tissue MapChart Type : Vector field plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : Physical
How does a continuous spatial depth gradient distribute across cells within a specific anatomical domain?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes best distinguish each spatial tissue domain?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Volcano plotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Which genes are most significantly differentially expressed between tumor and non-tumor cells?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How close are different cell types to each other?
View paper
Egbon O.A. et al. - 2025

Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations

Condition Dimension : Ordered : DiscreteData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedModality : SimulatedVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What trajectory structure connects different cell states during a biological transition process?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : CategoricalData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : Functional tissue unitVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which biological pathways are differentially enriched in specific spatial regions of a tissue?
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Does raw single-molecule imaging data confirm the co-localization of predicted interacting cells?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : CategoricalData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Chord diagramCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : CircularScalability Strategy : Summay/Aggregate
What are the key differences in co-occurrence patterns of functionally related genes within the detected modules when comparing AD and wild-type samples?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Network graphChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Force-directedLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Scalability Strategy : Summay/Aggregate
Do cell clusters derived from the reconstructed cell-level communication graph form coherent groupings in low-dimensional space?What is the spatial distribution of different cell types ?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
What are the spatial expression patterns of known marker genes for specific digestive tract regions?
View paper
Jiang Z. et al. - 2024

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a decomposition network

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which genes show differential expression across spatial domains, and what is the expression distribution per domain?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : SuperpositionLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the gene expression signatures differ across tissue regions?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : Ordered : ContinuosData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do the most dynamically expressed genes change along a developmental trajectory, and what patterns of up- and down-regulation do they follow over pseudotime?
View paper
Feng X. et al. - 2025

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How does the refined interaction network compare to the raw spatial graph in terms of cell-type communication strengths for the data?
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does a molecular or cellular process propagate across tissue space in a spatially ordered manner?
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
Which biological pathways are enriched among the receptors involved in predicted cell–cell interactions, and do these pathways differ between short-range and long-range communication modes?
View paper
Song X. et al. - 2025

QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
How many genes show interaction-dependent expression changes across different combinations of anchor and neighbor cell types?
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What is the spatial distribution of gene expression patterns in disease?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : No scalability strategy (Item-level)
Where are the co-expression modules between spatially variable genes?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Square bubble PlotLayout : LinearScalability Strategy : Summay/Aggregate
What are the biological processes that characterize the overall cell type identity of the cells belonging to the discovered module?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Spatial gridCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of gene expression measurements across tissue?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : BoxplotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Does the abundance of an immune cell subtype differ significantly across tumor regions?
View paper
Li Y. et al. - 2024

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Sankey diagramCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Summay/Aggregate
How do two different cell type classification schemes correspond to each other?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of the cells?
View paper
Li et al., 2023

Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial organization of tumor and normal tissue regions?
View paper
Li et al., 2023

Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How the methods classify the cells?What cell types are present?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Density PlotCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
How does a specific communication signal compare to the overall distribution of signals?
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What genes specifically mark each functional subtype within an immune cell population?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularResolution of observation : Field of viewVisualized Elements : ObservationBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Microenvironments & Cellular NichesSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are tumor neighborhoods and immune cells spatially organized in 3D?What is the 3D spatial organization of cell types in diseased tissue?
View paper
Liu W. et al. - 2023

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do spatially ordered gene expression gradients align with a computationally inferred pseudotime trajectory across tissue layers?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Navigating (Focus + Context)
Which cell types are present?
View paper
Bernstein M.N. et al. - 2022

SpatialCorr identifies gene sets with spatially varying correlation structure

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Force-directedLayout : Spatial : LatentScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How do gene expression patterns correlate across cell states?What is the developmental progression of cells?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
Which genes are differentially expressed across spatial tissue clusters, and do they show cluster-specific marker gene patterns?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the global spatial distribution of cell types across a tissue section as predicted by a deconvolution method?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : No abstractionChart Type : 3D ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cell type composition of the 3D reconstructed tissue?
View paper
Zhang et al., 2025

Winnow-KAN: single-cell RNA-seq location recovery with small-gene-set spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What are the cell distances?
View paper
Wang L. et al. - 2023

Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in tissue do specific gene pairs co-localize?
View paper
Liang Y. et al. - 2024

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the laminar organization of the tissue?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Geometric Proximity & Co-localizationAbstraction : CompleteChart Type : Line ChartCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : Summay/Aggregate
Which cell populations show spatially clustered vs random distributions and how does spatial clustering scale with distance?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Network graphCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types preferentially co-localize in space within a tissue?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Long et al., 2024

Deciphering spatial domains from spatial multi-omics with SpatialGlue

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Imaging-basedModality : Spatial proteomicsResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Violin plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Summay/Aggregate
How do marker genes distinguish cell types?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Does the influence of a specific cell type on gene expression vary spatially across tissue regions?
View paper
Yang J. et al. - 2024

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : MolecularAbstraction : CompleteChart Type : Spatial Tissue MapChart Type : Vector field plotCommunicative/Contextualization : No contextualizationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
View paper
Agrawal A. et al. - 2024

NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : CellularBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
How is the expression of key predicted ligand-receptor genes distributed across the cell types in the low-dimensional gene expression space?
View paper
Sriworarat et al., 2023

Performant web-based interactive visualization tool for spatially-resolved transcriptomics experiments

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Density PlotChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are spatially resolved gene expression measurements distributed across a tissue section?
View paper
Blampey Q. et al. - 2024

Sopa: a technology-invariant pipeline for analyses of image-based spatial omics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : MolecularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Flourescence tissue imageCommunicative/Contextualization : HighlightingComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution and expression pattern of specific cell types?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
In a defined area, which specific pathway activities are present?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Chord diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
Which cell types exchange the most short-range ligand-receptor signals with a given cell population?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Pang et al., 2025

STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Boundary & Interface DynamicsAbstraction : CompleteAbstraction : PartialChart Type : Dimensionality reductionChart Type : Spatial HeatmapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Can unsupervised clustering of spatial transcriptomics data recover biologically meaningful brain region boundaries?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : PseudotimeData Components : Spatial Coordinates : Native 2DData Components : TimeMetadata : Experimental : Biological statusMetadata : Experimental : TissueModality : Imaging-basedVisualized Elements : ObservationBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : ScatterplotChart Type : Vector field plotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the cellular differentiation trajectory in an injuryregion, and how is it organized spatially?
View paper
Sun D. et al. - 2022

STRIDE: Accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : Experimental : TissueModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How can multiple serial tissue sections be integrated to reconstruct the 3D spatial organization of cell types in a developing organ?
View paper
Higgins C. et al. - 2025

Spatial transcriptomics iterative hierarchical clustering (stIHC): A novel method for identifying spatial gene co-expression modules

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the characteristic spatial expression patterns of genes representative of each co-expression cluster?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Sampling/Filtering
What biological processes are significantly enriched among spatially variable genes identified in a tissue?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Which communication signals are strongest and shared across samples?
View paper
Zhang T. et al. - 2025

GAADE: identification spatially variable genes based on adaptive graph attention network

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Benjamin K. et al. - 2024

Multiscale topology classifies cells in subcellular spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Flourescence tissue imageChart Type : Spatial Tissue MapCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where are specific cell types spatially located in tissue based on imaging-based segmentation?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : Field of viewResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : Histological imageChart Type : Spatial gridCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How does the spatial organization of tissue appear at the histological level?What is the spatial distribution of gene expression measurements across tissue?
View paper
Zhang C. et al. - 2023

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HeatmapCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : LinearScalability Strategy : Sampling/Filtering
How do marker genes distinguish cortex layers from fiber tracts?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : TimeModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : RelationshipBiological : MolecularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : CompleteChart Type : UpSet plotCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
Which gene expression programs are shared or unique across different developmental stages or cell states?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a microenvironmental gene expression signature spatially distributed in tissue?
View paper
Wei R. et al. - 2022

Spatial charting of single-cell transcriptomes in tissues

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : scRNA-seqModality : Sequencing-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How is immune cell functional state spatially distributed within the tumor microenvironment?
View paper
Schmidt M. et al. - 2024

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Functional tissue unitResolution of observation : MolecularVisualized Elements : FeatureVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteAbstraction : PartialChart Type : BoxplotChart Type : Spatial HeatmapChart Type : TableCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)Scalability Strategy : Summay/Aggregate
Which genes and biological pathways define a co-expressed gene module, and how active is that module across different cell types and clusters?
View paper
Adhikari S.D. et al. - 2025

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : RelationshipBiological : CellularBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
What are the spatial domains?
View paper
Xu et al., 2022

DeepST: identifying spatial domains in spatial transcriptomics by deep learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : No abstractionChart Type : Dimensionality reductionChart Type : Dot ChartChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which are the differentially expresssed genes presnt in the sample?
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : RelationshipVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : CompleteChart Type : Bubble PlotChart Type : Venn diagramCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Force-directedScalability Strategy : Summay/Aggregate
How do gene modules overlap across spatial structures?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Other : Database
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the whole-brain expression pattern of a spatially filtered top gene?
View paper
Moehlin J. et al. - 2021

Inferring biologically relevant molecular tissue substructures by agglomerative clustering of digitized spatial transcriptomes with multilayer

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Spatial gridCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial patterns of specific gene expression in tissue?
View paper
Liu W. et al. - 2022

Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are distinct anatomical regions distributed across a tissue section, as identified by spatial transcriptomics clustering?
View paper
Aminu M. et al. - 2025

CoCo-ST detects global and local biological structures in spatial transcriptomics datasets

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Lineage & Trajectory InferenceAbstraction : PartialChart Type : Spatial Tissue MapChart Type : Vector field plotLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial trajectory of cancer progression across tissue?
View paper
Fang S. et al. - 2025

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Imaging-basedResolution of observation : MolecularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What biological functions are associated with shared versus regulon-specific target genes in a co-regulatory network?
View paper
Gui Y. et al. - 2024

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
Are the cell types observed as separated clusters in a low-dimensional visualization?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : TimeMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : Summay/Aggregate
What are the cell type identities present across developmental time points?
View paper
Andersson A. et al. - 2024

Points2Regions: Fast, interactive clustering of imaging-based spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : CellularAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Summay/Aggregate
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially distributed in a diseased tissue section?
View paper
Wang Z. et al. - 2025

MNiST: A deep learning framework for multi-scale spatial feature modeling and cellular landscape decoding in spatial

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularBiological : Systemic/IntegrativeGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How do cell type compositions change across developmentalstages?
View paper
Dong et al., 2021

Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialChart Type : Histological imageChart Type : Spatial Tissue MapCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the structure of the tissue?
View paper
Aggarwal B. and Sinha S. - 2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data

Condition Dimension : N/AModality : Imaging-basedResolution of observation : MolecularVisualized Elements : RelationshipBiological : IntercellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : PartialChart Type : Bubble PlotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the main biological function associated with the genes that define the discovered module?
View paper
Cable D.M. et al. - 2022

Robust decomposition of cell type mixtures in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Can a deconvolution method resolve fine-grained cell subtypes and assign them to specific spatial locations within a tissue?Do predicted spatial locations of cell subtypes match the observed expression of their defining marker genes?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : HexplotCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are cell type-specific gene signatures spatially distributed in tissue?
View paper
Zohora F.T. et al. - 2025

CellNEST reveals cell–cell relay networks using attention mechanisms on spatial transcriptomics

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotChart Type : Histological imageComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of disease subtypes?
View paper
Mah C.K. et al. - 2024

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : StatisticBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/Filtering
What latent patterns of RNA colocalization emerge across compartments, cells, and gene pairs when the colocalization tensor is decomposed?
View paper
Zhang C. et al. - 2023

STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DData Components : StatisticMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : MolecularAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Where in the tissue is a gene of interest expressed?
View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do spatially defined microenvironment signaling patterns distribute across a tissue section?
View paper
Wang M. et al. - 2023

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : Sampling/Filtering
Do known cortical layer marker genes show distinct expression patterns in a low-dimensional embedding that corresponds to transcriptional clusters?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Modality : Genomics
View paper
Jiang X. et al. - 2024

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedModality : Sequencing-based: Deconvolved dataResolution of observation : Multi-cellularVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Spatial Deconvolution & Resolution EnhancementAbstraction : CompleteChart Type : Bar plotCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cell type composition of each computationally identified spatial tissue domain?
View paper
Liu T. et al. - 2024

Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Anatomical & Spatial Domain DiscoveryAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the reference spatial organization of cortical layers in a tissue section used as ground truth for benchmarking spatial clustering methods?
View paper
Yu J. et al. - 2023

Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : HeatmapCommunicative/Contextualization : AnnotationComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/Filtering
Which genes are differentially expressed across spatial regions of a tumor?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do genes with spatially varying expression group into distinct spatial patterns across tissue regions?
View paper
Klein et al., 2025

Mapping cells through time and space with moscot

Condition Dimension : Ordered : DiscreteData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : Systemic/IntegrativeGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : Reference structureComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How do neuronal driver genes change in spatial expression across development?
View paper
Pont F. et al. - 2023

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Functional Enrichment & Pathway ActivityAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : AnnotationCommunicative/Contextualization : Reference structureComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are pathway activities spatially distributed in tissue?
View paper
Müller-Bötticher N. et al. - 2025

Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Sub-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell type distributed spatially throughout an organism?
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : HexplotCommunicative/Contextualization : AnnotationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a specific cell condition spatially distributed in tissue?
View paper
Li Z. and Zhou X. - 2022

BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : SampleModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteChart Type : Dimensionality reductionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cells group by gene expression when using a specific computational method?
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Condition Dimension : CategoricalData Components : StatisticMetadata : Experimental : DonorModality : ProteomicsResolution of observation : CellularVisualized Elements : StatisticBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Density PlotChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : SuperpositionLayout : LinearScalability Strategy : No scalability strategy (Item-level)
How do the relationships vary across patients and define imune infiltration patterns?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : 3D reconstructedMetadata : No metadataModality : Sequencing-based: Deconvolved dataResolution of observation : CellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Coordinate Registration & 3D ReconstructionAbstraction : PartialChart Type : 3D ScatterplotChart Type : Schematic anatomical diagramCommunicative/Contextualization : No contextualizationCommunicative/Contextualization : Reference structureComparative Design : No comparative designLayout : Spatial : Physical 3DScalability Strategy : Sampling/Filtering
How do computationally identified spatial domains align with established anatomical regions in a standard brain atlas?
View paper
Danaher P. et al. - 2025

InSituCor: exploring spatially correlated genes conditional on the cell type landscape

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : DonorMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Co-expression & Co-localized ModulesAbstraction : PartialChart Type : Spatial HeatmapCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene module expressed spatially in cancer cells in different tumors?
View paper
Li et al., 2023

SpaceWalker: Interactive Gradient Exploration for Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What spatial shape do transcriptomically similar neighborhoods take from different seed locations within a brain section?
View paper
Cable D.M. et al. - 2022

Cell type-specific inference of differential expression in spatial transcriptomics

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Tissue Architecture & MorphologyAbstraction : PartialCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How is a pathological feature spatially distributed across a disease tissue section?
View paper
Wang J. et al. - 2023

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Condition Dimension : N/AData Components : Biological AnnotationMetadata : No metadataModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationVisualized Elements : StatisticBiological : CellularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : CompleteChart Type : Pie ChartCommunicative/Contextualization : AnnotationComparative Design : No comparative designLayout : Space-fillingScalability Strategy : Summay/Aggregate
Which cell types are most represented among spatially variable genes identified in a tissue?
View paper
Thuilliez C. et al. - 2024

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : Imaging-basedResolution of observation : CellularVisualized Elements : ObservationGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonChart Type : Dimensionality reductionCommunicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : LatentScalability Strategy : No scalability strategy (Item-level)
How do cancer sub-populations separate in embedding space after sub-clustering?
View paper
Ye et al., 2023

Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : Bar plotChart Type : HexplotChart Type : Histological imageCommunicative/Contextualization : HighlightingCommunicative/Contextualization : Reference structureComparative Design : Explicit encodingComparative Design : SuperpositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)Other : UI / Screenshot
How can multiple spatial omics data layers be simultaneously visualized in their tissue context to reveal distinct regional gene expression patterns?
View paper
Wang et al., 2025

SOAPy: a Python package to dissect spatial architecture, dynamics, and communication

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : TissueResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : RelationshipVisualized Elements : StatisticBiological : IntercellularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Cell–Cell Communication & SignalingAbstraction : CompleteChart Type : Dot ChartCommunicative/Contextualization : HighlightingComparative Design : Explicit encodingLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Which specific ligand-receptor pairs are most significantlyactive between a given pair of cell types?
View paper
Niyakan S. et al. - 2024

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : AnnotationComparative Design : JuxtapositionLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue morphology look like across multiple samples from the same organ?
View paper
Niu J. et al. - 2024

Deep clustering representation of spatially resolved transcriptomics data using multi-view variational graph auto-encoders with consensus clustering

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionAbstraction : PartialChart Type : ScatterplotChart Type : Spatial Gene Expression MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
Do identified spatial domains have distinct marker genes that validate their biological identity?
View paper
Palla et al., 2022

Squidpy: a scalable framework for spatial omics analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Sequencing-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Spatially Variable Feature DiscoveryAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : HighlightingComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What are the spatial expression patterns of the most spatially variable genes in a tissue section, and do they correspond to specific cell types?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureVisualized Elements : ObservationBiological : MolecularGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringOther : UI / Screenshot
Which genes are specifically expressed in spatial domains?
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : No metadataModality : scRNA-seq
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the spatial distribution of Aβ plaques and cells in diseased tissue?
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : ObservationVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : CompleteAbstraction : PartialChart Type : BoxplotChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
How are cell populations and marker genes distributed in specific tissue regions?
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

Modality : Genomics
View paper
Shang L. et al. - 2025

Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : FeatureVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
What are the spatial expression patterns of metagenes across tumor regions?
View paper
Jiang X. et al. - 2022

A Bayesian modified Ising model for identifying spatially variable genes from spatial transcriptomics data

Condition Dimension : N/AData Components : Spatial Coordinates : Native 2DMetadata : No metadataResolution of observation : Field of viewVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What is the histological appearance of the tissue section?
View paper
Allam et al., 2021

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Condition Dimension : CategoricalData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateModality : Imaging-basedResolution of observation : Sub-cellularBiological : CellularBiological : Systemic/IntegrativeBiological : TissueGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : PartialChart Type : Spatial Gene Expression MapChart Type : Topology plot (3D)Communicative/Contextualization : AnnotationCommunicative/Contextualization : HighlightingComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
Is there a diference between the distribution of key markes in healthy and diseased tissues?
View paper
Yu S. and Li W. - 2024

spVC for the detection and interpretation of spatial gene expression variation

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Sequencing-basedResolution of observation : Multi-cellularVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : Spatial Tissue MapCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How are different cell types spatially distributed across tissue regions
View paper
Yang et al., 2024

SRT-Server: powering the analysis of spatial transcriptomic data

Condition Dimension : CategoricalData Components : Spatial Coordinates : Native 2DMetadata : Experimental : SampleModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationVisualized Elements : Tissue unit/StructureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionChart Type : Histological imageCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
What does the tissue morphology look like in the breast cancer sample?
View paper
Fu Y.C. et al. - 2024

scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : Disease stateMetadata : Experimental : TissueModality : Imaging-basedResolution of observation : CellularVisualized Elements : StatisticBiological : TissueGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : CompleteChart Type : Stacked bar chartCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : LinearScalability Strategy : Summay/Aggregate
What is the cellular composition of spatial neighborhoods for diseased cells?
View paper
Wang G. et al. - 2023

Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks

Condition Dimension : N/AData Components : Biological AnnotationData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : Functional tissue unitVisualized Elements : ObservationBiological : TissueGeneral Analytical Domains : Spatiotemporal Dynamics & PerturbationsSpecific Analytical Domains : Evolving Biological ProcessesAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : HighlightingCommunicative/Contextualization : No contextualizationComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
What is the spatial distribution of cell types in the embryonic heart as measured by a high-resolution spatial sequencing platform?
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : No metadataModality : Imaging-basedResolution of observation : Field of viewVisualized Elements : FeatureVisualized Elements : ObservationBiological : CellularGeneral Analytical Domains : Spatial Entity & Domain IdentificationSpecific Analytical Domains : Cell-Type & Cell-State MappingAbstraction : PartialChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : No scalability strategy (Item-level)
How are cell types spatially distributed across a tissue section?
View paper
Dries et al., 2021

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : 3D reconstructedData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Imaging-basedModality : ProteomicsResolution of observation : CellularVisualized Elements : ObservationBiological : CellularAbstraction : CompleteAbstraction : PartialChart Type : 3D ScatterplotChart Type : Dimensionality reductionCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionLayout : Spatial : LatentLayout : Spatial : PhysicalScalability Strategy : Summay/Aggregate
View paper
Ma Y. and Zhou X. - 2024

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics

Condition Dimension : CategoricalData Components : Biological AnnotationData Components : Gene Expression MatrixMetadata : Experimental : Disease stateModality : Sequencing-basedResolution of observation : Field of viewVisualized Elements : FeatureBiological : Systemic/IntegrativeGeneral Analytical Domains : Comparative & Multi-Dataset IntegrationSpecific Analytical Domains : Cross-Sample & Cross-Condition ComparisonAbstraction : CompleteChart Type : Bar plotComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : LinearScalability Strategy : Sampling/FilteringScalability Strategy : Summay/Aggregate
Are gene expression levels in specific tissue domains altered ina disease condition compared to controls?
View paper
Kim H. et al. - 2023

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data

Condition Dimension : N/AData Components : Biological AnnotationData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DMetadata : Experimental : TissueModality : Sequencing-basedResolution of observation : CellularVisualized Elements : ObservationBiological : IntercellularBiological : MolecularGeneral Analytical Domains : Spatial Relational NetworksSpecific Analytical Domains : Microenvironments & Cellular NichesAbstraction : No abstractionChart Type : ScatterplotChart Type : Spatial Gene Expression MapChart Type : Spatial Tissue MapCommunicative/Contextualization : HighlightingComparative Design : No comparative designLayout : Spatial : PhysicalScalability Strategy : Navigating (Focus + Context)
What genes are expressed in cells based on their neighboring cell types?
View paper
Ma Y. et al. - 2024

HyperGCN: an effective deep representation learning framework for the integrative analysis of spatial transcriptomics data

Condition Dimension : N/AData Components : Gene Expression MatrixData Components : Spatial Coordinates : Native 2DModality : Imaging-basedResolution of observation : CellularVisualized Elements : FeatureBiological : TissueGeneral Analytical Domains : Molecular & Functional LandscapesSpecific Analytical Domains : Targeted Feature ExpressionAbstraction : No abstractionChart Type : ScatterplotCommunicative/Contextualization : No contextualizationComparative Design : JuxtapositionComparative Design : Juxtaposition : Small multiplesLayout : Spatial : PhysicalScalability Strategy : Sampling/Filtering
How is a gene expressed across the tissue?
View paper
Liu T. et al. - 2024

Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep

Modality : Spatial proteomics
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Modality : scRNA-seq
View paper
Zheng et al., 2022

Aquila: a spatial omics database and analysis platform

Other : UI / Screenshot
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Modality : scRNA-seq
View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Modality : scRNA-seq
View paper
Yuan Z. et al. - 2023

SODB facilitates comprehensive exploration of spatial omics data

View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Modality : scRNA-seq
View paper
Raredon M.S.B. et al. - 2023

Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES

Modality : scRNA-seq
View paper
Gong C. et al. - 2024

SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

Other : UI / Screenshot
View paper
Zheng et al., 2022

Aquila: a spatial omics database and analysis platform

Other : UI / Screenshot
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Modality : scRNA-seq
View paper
Zheng et al., 2022

Aquila: a spatial omics database and analysis platform

Other : UI / Screenshot
View paper
Pham et al., 2023

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

View paper
Gong C. et al. - 2024

SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

Other : UI / Screenshot
View paper
Ruan Z. et al. - 2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Modality : scRNA-seq
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Modality : scRNA-seq
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Modality : scRNA-seq
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Modality : scRNA-seq
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Modality : scRNA-seq
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Modality : scRNA-seq
View paper
Xia T. et al. - 2025

Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser

View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Modality : scRNA-seq
View paper
Wan X. et al. - 2023

Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope

Modality : scRNA-seq
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Other : UI / Screenshot
View paper
Liu et al., 2025

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Modality : scRNA-seq
View paper
Raghavan V. et al. - 2025

Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics

Modality : scRNA-seq
View paper
Bhuva D.D. et al. - 2024

vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis

Modality : scRNA-seq
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Other : Photo
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Other : UI / Screenshot
View paper
Liu T. et al. - 2024

Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep

Modality : Spatial proteomics
View paper
Liu T. et al. - 2024

Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep

Modality : Spatial proteomics
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Other : UI / Screenshot
View paper
Biran H. et al. - 2024

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Modality : scRNA-seq
View paper
Li X. et al. - 2025

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

Other : UI / Screenshot
View paper
Pirrotta S. et al. - 2024

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Modality : scRNA-seq
View paper
Jing Z. et al. - 2024

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Other : Photo
View paper