Identifying cell-type-specific spatially variable genes with ctSVG

Spatially variable genes (SVGs) reveal the molecular and functional heterogeneity of cells across different spatial regions of a tissue. Sample-wide SVGs identified by existing methods largely overlap with cell-type marker genes derived from single-cell gene expression, leaving the spatial location information largely underutilized. We develop ctSVG, a computational method specifically tailored for Visium HD spatial transcriptomics at single-cell resolution. We show that cell-type-specific SVGs identified by ctSVG include many new genes that do not overlap with sample-wide SVGs or cell-type marker genes and that these genes reveal important biological functions in real spatial datasets.