UC Irvine

Cells work in concert to perform functions in a multicellular organism. This coordinationoccurs through cell–cell communication (CCC), where cells exchange molecular messages. CCC is fundamental to numerous biological processes, such as cell growth, division, differentiation, tissue and organ development, and disease progression. Recent technological breakthroughs in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics have revolutionized the study of CCC. While a rich number of methods have been developed to infer CCC, the underlying patterns and structures within cell communication events remain insufficiently understood. In Chapter 1, we reviewed the vast number of methods that have been developed to infer CCC based on scRNA-seq or spatial transcriptomics datasets. In Chapter 2, we analyzed the diversity of CCC networks within different disease conditions. We proposed measures at 3 scales, including node-level, edge-level, and graph-level, that comprehensively analyzes CCC networks at different levels. In Chapter 3, we proposed CrossChat, which composed of two core methods, CrossChatH and Cross- ChatT, to detect and analyze hierarchical structures within CCC with respect to ligand and receptor expression in two complementary angles. In Chapter 4, we applied CrossChat to scRNA-seq and spatial transcriptomics datasets to illustrate its functionalities and showcase its novelty over existing CCC methods.