Chen HM, MacDonald JA. Network analysis of TCGA and GTEx gene expression datasets for identification of trait-associated biomarkers in human cancer.
STAR Protoc 2022;
3:101168. [PMID:
35199033 PMCID:
PMC8841814 DOI:
10.1016/j.xpro.2022.101168]
[Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Advances in high-throughput sequencing technologies now yield unprecedented volumes of OMICs data with opportunities to conduct systematic data analyses and derive novel biological insights. Here, we provide protocols to perform differential-expressed gene analysis of TCGA and GTEx RNA-Seq data from human cancers, complete integrative GO and network analyses with focus on clinical and survival data, and identify differential correlation of trait-associated biomarkers.
For complete details on the use and execution of this protocol, please refer to Chen and MacDonald (2021).
Protocols for the identification of trait-associated molecular correlates in cancer
Differentially-expressed gene (DEG) analysis of TCGA and GTEx transcriptomic data
Protocols for integrative network analysis of RNA-seq, clinical, and survival data
Differential correlation of trait-associated biomarkers for hypothesis testing
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