Protocol for analyzing functional gene module perturbation during the progression of diseases using a single-cell Bayesian biclustering framework.

STAR Protoc

Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China; SJTU-Yale Joint Center for Biostatistics and Data Science Organization, Shanghai Jiao Tong University, Shanghai, China; Center for Biomedical Data Science, Translational Science Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address:

Published: December 2024

The pathogenesis of complex diseases involves intricate gene regulation across cell types, necessitating a comprehensive analysis approach. Here, we present a protocol for analyzing functional gene module (FGM) perturbation during the progression of diseases using a single-cell Bayesian biclustering (scBC) framework. We describe steps for setting up the scBC workspace, preparing and exploring input data, training the model, and reconstructing the data matrix. We then detail procedures for Bayesian biclustering, exploring biclustering results, and uncovering pathway perturbations. For complete details on the use and execution of this protocol, please refer to Gong et al..

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11472622PMC
http://dx.doi.org/10.1016/j.xpro.2024.103349DOI Listing

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