ScBSP: A fast and accurate tool for identifying spatially variable features from high-resolution spatial omics data.

ABSTRACT: Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in two and three-dimensional space. However, sparse sequencing capacity and growing spatial resolution in spatial omics present significant computational challenges in identifying biologically meaningful molecules that exhibit variable spatial distributions across different omics. We introduce scBSP, an open-source, versatile, and user-friendly package for identifying spatially variable features in high-resolution spatial omics data. scBSP leverages sparse matrix operation to significantly increase computational efficiency in both computational time and memory usage. In diverse spatial sequencing data and simulations, scBSP consistently a

SUBMITTER: Li J 

PROVIDER: S-EPMC11838397 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature