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MetaNetwork: Enhancing biological interpretation of proteomics data with weighted gene correlation network analysis (WGCNA)

• Downloading MetaNetwork
• Using MetaNetwork
• Vignette 1: Module eigenprotein analysis
• Vignette 2: Enhancing Differential Expression Analysis with MetaNetwork

MetaNetwork is a free, open-source, R-based application that performs weighted gene correlation network analysis on proteomics data (WGCNA). WGCNA creates networks of proteins that are correlated across samples and uses unsupervised clustering to group proteins into "modules." Each module contains groups of proteins that represent biological pathway. These pathways can be identified using MetaNetwork's gene ontology enrichment analysis.

Getting started

The Downloading MetaNetwork and Using MetaNetwork pages detail how to use MetaNetwork.

Additionally, this wiki provides two vignettes for understanding how to use both the WGCNA and Allez gene ontology enrichment analysis. Vignette 1 goes over how to use eigenprotein analysis to interpret proteomics data, and Vignette 2 demonstrates how MetaNetwork's GO Enrichment feature can be used to identify the biological function of modules.