WGCNA: An R Package for Weighted Correlation Network Analysis¶
Langfelder, P., & Horvath, S. (2008). WGCNA: An R Package for Weighted Correlation Network Analysis. BMC Bioinformatics.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Feature Clustering
- Feature Clustering, here Weighted Gene Co-expression Network Analysis (WGCNA), groups the 20,000 genes into about fifteen modules of co-expressed genes and summarizes each module by its module eigengene, the single dominant expression pattern that represents the group.
This sourceExplains that WGCNA summarizes each co-expression module by a module eigengene, the first principal component representing its dominant expression profile.
- Feature Clustering, here Weighted Gene Co-expression Network Analysis (WGCNA), groups the 20,000 genes into about fifteen modules of co-expressed genes and summarizes each module by its module eigengene, the single dominant expression pattern that represents the group.
Verification¶
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Does it back the claim? Not recorded. The single citation of this work carries no recorded support check.
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Registry ID ref:f069d8288155 · see in the full table