Comparative analysis of cell-cell communication at single-cell resolution.

ABSTRACT: Inference of cell-cell communication from single-cell RNA sequencing data is a powerful technique to uncover intercellular communication pathways, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell-level information. Here we present Scriabin, a flexible and scalable framework for comparative analysis of cell-cell communication at single-cell resolution that is performed without cell aggregation or downsampling. We use multiple published atlas-scale datasets, genetic perturbation screens and direct experimental validation to show that Scriabin accurately recovers expected cell-cell communication edges and identifies communication networks that can be obscured by agglomerative methods. Additionally, we use spatial transcriptomic data t

SUBMITTER: Wilk AJ 

PROVIDER: S-EPMC10638471 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature