GAADE: identification spatially variable genes based on adaptive graph attention network.

ABSTRACT: The rapid advancement of spatial transcriptomics (ST) sequencing technology has made it possible to capture gene expression with spatial coordinate information at the cellular level. Although many methods in ST data analysis can detect spatially variable genes (SVGs), these methods often fail to identify genes with explicit spatial expression patterns due to the lack of consideration for spatial domains. Considering spatial domains is crucial for identifying SVGs as it focuses the analysis of gene expression changes on biologically relevant regions, aiding in the more accurate identification of SVGs associated with specific cell types. Existing methods for identifying SVGs based on spatial domains predefine spot similarity before training, which prevents adaptive learning and limits genera

SUBMITTER: Zhang T 

PROVIDER: S-EPMC11658817 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature