Randomized Spatial PCA (RASP): a computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics data.

ABSTRACT: Spatial transcriptomics (ST) provides critical insights into the complex spatial organization of gene expression in tissues, enabling researchers to unravel the intricate relationship between cellular environments and biological function. Identifying spatial domains within tissues is essential for understanding tissue architecture and the mechanisms underlying various biological processes, including development and disease progression. Here, we present Randomized Spatial PCA (RASP), a novel spatially aware dimensionality reduction method for spatial transcriptomics (ST) data. RASP is designed to be orders-of-magnitude faster than existing techniques, scale to ST data with hundreds-of-thousands of locations, support the flexible integration of non-transcriptomic covariates, and enable the r

SUBMITTER: Gingerich IK 

PROVIDER: S-EPMC11703158 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature