Weighted gene coexpression network analysis: state of the art

J Biopharm Stat. 2010 Mar;20(2):281-300. doi: 10.1080/10543400903572753.

Abstract

Weighted gene coexpression network analysis (WGCNA) has been applied to many important studies since its introduction in 2005. WGCNA can be used as a data exploratory tool or as a gene screening method; WGCNA can also be used as a tool to generate testable hypothesis for validation in independent data sets. In this article, we review key concepts of WGCNA and some of its applications in gene expression analysis of oncology, brain function, and protein interaction data.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Bayes Theorem
  • Brain / metabolism
  • Data Interpretation, Statistical
  • Gene Expression Profiling / statistics & numerical data*
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • Humans
  • Models, Statistical*
  • Oligonucleotide Array Sequence Analysis / statistics & numerical data*
  • Pan troglodytes
  • Protein Interaction Mapping / statistics & numerical data*
  • RNA, Messenger / metabolism
  • Species Specificity

Substances

  • RNA, Messenger