Cell–cell interactions orchestrate organismal development, homeostasis and single-cell functions. When cells do not properly interact or improperly decode molecular messages, disease ensues. Thus, the identification and quantification of intercellular signalling pathways has become a common analysis performed across diverse disciplines. The expansion of protein–protein interaction databases and recent advances in RNA sequencing technologies have enabled routine analyses of intercellular signalling from gene expression measurements of bulk and single-cell data sets. In particular, ligand–receptor pairs can be used to infer intercellular communication from the coordinated expression of their cognate genes. In this Review, we highlight discoveries enabled by analyses of cell–cell interactions from transcriptomic data and review the methods and tools used in this context.

细胞与细胞的相互作用协调有机体的发育、体内平衡和单细胞功能。当细胞不能正确相互作用或不能正确解码分子信息时，疾病就会随之而来。因此，细胞间信号通路的识别和定量已成为跨学科的常见分析。蛋白质-蛋白质相互作用数据库的扩展和RNA测序技术的最新进展使得可以通过大量和单细胞数据集的基因表达测量来对细胞间信号传导进行常规分析。特别是，配体-受体对可用于从其同源基因的协调表达推断细胞间通讯。在这篇综述中，我们重点介绍了通过转录组数据分析细胞与细胞相互作用所获得的发现，并回顾了在此背景下使用的方法和工具。