Spatial Transcriptomics


GenePattern provides support for the visualization and analysis of spatially-resolved transcriptomics data, such as those generated with 10X Visium, through the release of the spatialGE modules.

The following modules are provided.

spatialGE.Preprocessing

Performs data ingestion, filtering, transformation, and pseudobulk operations to prepare data for downstream analysis in platforms such as GeoMx, Visium, and CosMx-SMI.

spatialGE.STplot

Generates plots displaying gene expression, cluster memberships and metadata within a spatial context. For best use, data from spatialGE.Preprocessing, spatialGE.STenrich, spatialGE.STclust or spatialGE.STdiff should be sent to spatialGE.STplot.Launcher.

spatialGE.SpatialAutocorrelation

Assesses the level of spatial uniformity in gene expression by calculating Moran’s I and/or Geary’s C and qualitatively explore correlations with sample-level metadata (i.e., tissue type, therapy, disease status). It is used to explore the relationship between a clinical (sample-level) variable of interest and the level of gene expression spatial uniformity within a sample.

spatialGE.STenrich

Detects genes showing spatial expression patterns (e.g., hotspots) and tests if spots/cells with a high average expression of a gene set show evidence of spatial aggregation.

spatialGE.STclust

Performs clustering analysis on spatial gene expression data.

spatialGE.STdiff

Performs differential expression analysis on spatial transcriptomics data. Identifies differentially expressed genes based on spatial and non-spatial models.

spatialGE.STgradient

Reads the output of spatialGE.STclust and then launches an analysis to test for genes for which there is evidence of expression spatial gradients with respect to a "reference" tissue niche/domain (e.g., higher expression closer to reference tissue niche, lower expression as farther from reference tissue niche).

Modules

View GenePattern spatial transcriptomics modules