STModule: identifying tissue modules to uncover spatial components and characteristics of transcriptomic landscapes - Ran Wang; Yan Qian; Xiaojing Guo; Fangda Song; Zhiqiang Xiong; Shirong Cai; Xiuwu Bian; Man Hon Wong; Qin Cao; Lixin Cheng; Gang Lu; Kwong Sak Leung (Genome Medicine)
Abstract Here we present STModule, a Bayesian method developed to identify tissue modules from spatially resolved transcriptomics that reveal spatial components and essential characteristics of tissues. STModule uncovers diverse expression signals in transcriptomic landscapes such as cancer, intraepithelial neoplasia, immune infiltration, outcome-related molecular features and various cell types, which facilitate downstream analysis and provide insights into tumor microenvironments, disease mechanisms, treatment development, and histological organization of tissues. STModule captures a broader spectrum of biological signals compared to other methods and detects novel spatial components. The tissue modules characterized by gene sets demonstrate greater robustness and transferability across different biopsies. STModule: https://github.com/rwang-z/STModule.git .