Barts Cancer Institute, Queen Mary University of London, London, UK.
Wellcome Sanger Institute, Cambridgeshire, UK.
Methods Mol Biol. 2021;2346:1-10. doi: 10.1007/7651_2020_343.
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.
细胞间通讯对于多细胞生物的发育和组织稳态至关重要。单细胞转录组学已经成为一种革命性的技术，可以通过配体-受体对来剖析细胞组成和潜在的细胞间通讯事件。为了系统地表征细胞间通讯，我们开发了一种框架，使用单细胞转录组学数据来绘制通过配体-受体相互作用介导的细胞间通讯事件。我们的配体、受体及其相互作用的知识库与一种计算方法相结合，以识别细胞类型特异性和生物学相关的相互作用。在这里，我们总结了我们知识库的结构和内容，并提供了从单细胞 RNA 测序数据推断细胞间通讯网络的实用指南。
