Robust identification of cell-cell communication heterogeneity in single cells

Cell-cell communication modulates cell fate decisions by relaying information across tissues and inducing intracellular responses mediated by gene regulatory networks. Although the inference of cell-cell communication from high-throughput data is gaining popularity, studying how communication pathways operate across biological scales and influence cell fate decisions remains challenging. Here, we present scRICH (robust identification of cell-cell communication heterogeneity in single cells), a computational framework that leverages single-cell and spatial transcriptomics data to unravel the heterogeneity of communication behavior within cell types, link cell-cell communication to cell fate decisions by incorporating dynamical information on RNA splicing, and connect cell-cell interactions with intracellular responses by constructing multilayer regulatory networks. We validate scRICH with new experiments on epidermal growth factor (EGF) ligand/receptor co-expression in keratinocytes, comparing these predictions against those of existing communication inference methods. Applying scRICH to multiple biological scenarios demonstrates its ability to capture relationships between distinct communication pathways and emerging trends along cell differentiation lineages and in space. A record of this paper's transparent peer review process is included in the supplemental information.