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).
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In a nutshell
- Select a trait via the dropdown menu. Identified modules will be
related to this trait
- 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.
- Press run
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