Wang Kunyue, Gong Yuqiao, Yan Zixin, Dang Zhiyuan, Wang Junhao, Wu Maoying, Zhang Yue
Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
STAR Protoc. 2024 Dec 20;5(4):103349. doi: 10.1016/j.xpro.2024.103349. Epub 2024 Sep 30.
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..
复杂疾病的发病机制涉及跨细胞类型的复杂基因调控,因此需要一种全面的分析方法。在此,我们提出了一种使用单细胞贝叶斯双聚类(scBC)框架分析疾病进展过程中功能基因模块(FGM)扰动的方案。我们描述了设置scBC工作区、准备和探索输入数据、训练模型以及重建数据矩阵的步骤。然后,我们详细介绍了贝叶斯双聚类、探索双聚类结果以及揭示通路扰动的程序。有关此方案的使用和执行的完整详细信息,请参考龚等人的研究。