CellSP: Module discovery and visualization for subcellular spatial transcriptomics data

Spatially resolved transcriptomics has made it possible to study the subcellular organization of mRNA, a critical aspect of cellular function. However, there is a dearth of analytical tools to identify and interpret the functional significance of subcellular spatial distribution patterns. To address this, we present CellSP, a computational framework for identifying, visualizing, and characterizing consistent subcellular spatial patterns of mRNA. CellSP introduces the concept of “gene-cell modules” to uncover gene sets with non-random subcellular transcript distributions in many cells. CellSP provides intuitive visualizations of the captured patterns and offers functional insights into genes and cells comprising each discovered module. We demonstrate that CellSP reliably identifies functionally significant modules across various tissues and reveals subcellular changes associated with phenotypic variation.