Integrated Cancer Research Center, School of Biological Sciences, Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, 315 Ferst Drive, Atlanta, GA 30619, USA.
STAR Protoc. 2022 Jun 2;3(2):101432. doi: 10.1016/j.xpro.2022.101432. eCollection 2022 Jun 17.
We describe a consensus approach for network construction based on fully conserved gene-gene interactions from randomly downsampled data subsets for an unbiased differential analysis of gene co-expression networks. The pipeline allows users to identify network nodes lost, conserved, and acquired in cancer as well as interpret the functional significance of these network changes. For proof of concept, the protocol is used to leverage RNA-seq data of tumor samples from TCGA and healthy tissue samples from the GTEx database. For complete details on the use and execution of this protocol, please refer to Arshad and McDonald (2021).
我们描述了一种基于从随机下采样数据子集中完全保守的基因-基因相互作用构建网络的共识方法，用于对基因共表达网络进行无偏差异分析。该流程允许用户识别癌症中丢失、保守和获得的网络节点，并解释这些网络变化的功能意义。为了验证概念，该方案利用了 TCGA 肿瘤样本和 GTEx 数据库中健康组织样本的 RNA-seq 数据。有关此方案的使用和执行的详细信息，请参阅 Arshad 和 McDonald（2021 年）。
