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Weighted Correlation Network Analysis (WGCNA)

Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated features (e.g. genes), for relating modules to external sample traits (using eigengene network methodology), and for calculating module membership measures. Relating modules instead of individual features to a sample trait can alleviate the multiple testing problem. Correlation networks facilitate network based screening methods that can be used to identify candidate biomarkers or therapeutic targets (reference).

In a nutshell

  1. Select a trait via the dropdown menu. Identified modules will be related to this trait
  2. Use the filter option to set the number of features included in the analysis. WGCNA is computational expensive and the maximal number of features that can be included in the analysis is therefore limited to 10,000.
  3. Press run