Identifying spatially variable genes by projecting to morphologically relevant curves.

ABSTRACT: Spatial transcriptomics enables high-resolution gene expression measurements while preserving the two-dimensional spatial organization of the biological sample. A common objective in spatial transcriptomics data analysis is to identify spatially variable genes within predefined cell types or regions within the tissue. However, these regions are often implicitly one-dimensional, making standard two-dimensional coordinate-based methods less effective as they overlook the underlying tissue organization. Here we introduce a methodology grounded in spectral graph theory to elucidate a one-dimensional curve that effectively approximates the spatial coordinates of the examined sample. This curve is then used to establish a new coordinate system that reflects tissue morphology. We then develop a g

SUBMITTER: Nicol PB 

PROVIDER: S-EPMC11601533 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature