Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk.

ABSTRACT: Spatially resolved transcriptomics provides genetic information in space toward elucidation of the spatial architecture in intact organs and the spatially resolved cell-cell communications mediating tissue homeostasis, development, and disease. To facilitate inference of spatially resolved cell-cell communications, we here present SpaTalk, which relies on a graph network and knowledge graph to model and score the ligand-receptor-target signaling network between spatially proximal cells by dissecting cell-type composition through a non-negative linear model and spatial mapping between single-cell transcriptomic and spatially resolved transcriptomic data. The benchmarked performance of SpaTalk on public single-cell spatial transcriptomic datasets is superior to that of existing inference met

SUBMITTER: Shao X 

PROVIDER: S-EPMC9338929 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature