STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics.

ABSTRACT: One of the major challenges in spatial transcriptomics is to detect spatially variable genes (SVGs), whose expression patterns are non-random across tissue locations. Many SVGs correlate with cell type compositions, introducing the concept of cell type-specific SVGs (ctSVGs). Existing ctSVG detection methods treat cell type-specific spatial effects as fixed effects, leading to tissue spatial rotation-dependent results. Moreover, SVGs may exhibit random spatial patterns within cell types, meaning an SVG is not always a ctSVG, and vice versa, further complicating detection. We propose STANCE, a unified statistical model for both SVGs and ctSVGs detection under a linear mixed-effect model framework that integrates gene expression, spatial location, and cell type composition information. STANC

SUBMITTER: Su H 

PROVIDER: S-EPMC11842841 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature