Inference of Ligand–Receptor Pairs from Single-Cell Transcriptomics Data

Abstract

Cell–cell communication is crucial for development and tissue homeostasis in multicellular organisms. Single-cell transcriptomics has emerged as a revolutionary technique for dissecting cellular compositions and potential cell–cell communication events via ligand–receptor pairs. To provide a systematic characterization of intercellular communication, we developed a framework to map cell–cell communication events mediated by ligand–receptor interactions across different cell types using single-cell transcriptomics data. Our repository of ligands, receptors and their interactions is integrated with a computational approach to identify cell-type specific and biologically relevant interactions. Here, we summarize the structure and content of our repository and present a practical guide for inferring cell–cell communication networks from single-cell RNA sequencing data.