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/PMC11472622 | PMC |
http://dx.doi.org/10.1016/j.xpro.2024.103349 | DOI Listing |
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