Prognostic genes of breast cancer revealed by gene co-expression network analysis.

ABSTRACT: The aim of the present study was to identify genes that may serve as markers for breast cancer prognosis by constructing a gene co-expression network and mining modules associated with survival. Two gene expression datasets of breast cancer were downloaded from ArrayExpress and genes from these datasets with a coefficient of variation >0.5 were selected and underwent functional enrichment analysis with the Database for Annotation, Visualization and Integration Discovery. Gene co-expression networks were constructed with the WGCNA package in R. Modules were identified from the network via cluster analysis. Cox regression was conducted to analyze survival rates. A total of 2,669 genes were selected, and functional enrichment analysis of them revealed that they were mainly associated with the

SUBMITTER: Shi H 

PROVIDER: S-EPMC5649579 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature