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Network analysis of TCGA and GTEx gene expression datasets for identification of trait-associated biomarkers in human cancer

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...

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Detalles Bibliográficos
Autores principales: Chen, Huey-Miin, MacDonald, Justin A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841814/
https://www.ncbi.nlm.nih.gov/pubmed/35199033
http://dx.doi.org/10.1016/j.xpro.2022.101168
Descripción
Sumario: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).