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Updated: May 24, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
STModule: identifying tissue modules to uncover spatial components and characteristics of transcriptomic landscapes
Ran Wang1,2,3, Yan Qian4, Xiaojing Guo5
1CUHK-SDU Joint Laboratory on Reproductive Genetics, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, 999077, China.
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 .

