HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics.

ABSTRACT: Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higher F1 scores (average F1 Score=0.948), improved computational efficiency, scalability, and reduced false positives (FPs). Through analysis of twelve real datasets from various spatial transcriptomic technologies, HEARTSVG identifies a greater number of biologically significant SVGs (average AUC = 0.792) than other comparative me

SUBMITTER: Yuan X 

PROVIDER: S-EPMC11228050 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature