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BMCBI
2008

WGCNA: an R package for weighted correlation network analysis

14 years 6 days ago
WGCNA: an R package for weighted correlation network analysis
Background: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate p...
Peter Langfelder, Steve Horvath
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Peter Langfelder, Steve Horvath
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