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A Protocol for Weighted Gene Co-expression Network Analysis With Module Preservation and Functional Enrichment
Phuong Nguyen1,2, Erliang Zeng1,2,3
1Division of Biostatistics and Computational Biology, College of Dentistry and Dental Clinics, University of Iowa, Iowa City, IA, USA.
Bio-Protocol
|September 26, 2025
Summary
This study introduces a Weighted Gene Co-expression Network Analysis (WGCNA) protocol for comparing paired tumor and normal gene expression data. It identifies conserved and disrupted gene modules, enhancing understanding of cancer pathogenesis and universal biological processes.
Area of Science:
- Transcriptomics
- Bioinformatics
- Systems Biology
Background:
- Weighted Gene Co-expression Network Analysis (WGCNA) is crucial for identifying gene modules in transcriptomic studies.
- Existing WGCNA protocols often lack methods for comparing module stability across different conditions.
- Understanding gene expression changes in paired tumor and normal tissues is vital for disease mechanism research.
Purpose of the Study:
- To present a comprehensive protocol for constructing and comparing WGCNA modules in paired tumor and normal datasets.
- To enable the identification of gene modules involved in both fundamental biological processes and cancer-specific pathogenesis.
- To provide a framework for module preservation analysis in paired data for deeper insights into disease molecular underpinnings.
Main Methods:
- Developed a step-by-step Weighted Gene Co-expression Network Analysis (WGCNA) protocol.
- Incorporated module preservation and functional enrichment analysis using TCGA cancer data.
- Preprocessed gene expression data and performed downstream network analysis for paired normal and tumor tissues.
Main Results:
- Demonstrated network differences between normal and tumor tissues using the WGCNA protocol.
- Enabled identification of conserved and disrupted gene co-expression modules across conditions.
- Provided a framework for analyzing module stability and functional relevance in paired datasets.
Conclusions:
- The presented WGCNA protocol facilitates the comparison of gene modules in paired datasets, distinguishing core biological processes from disease-specific alterations.
- This approach enhances the understanding of oral cancer and other diseases by revealing conserved and disrupted molecular networks.
- The protocol offers a valuable tool for researchers investigating gene co-expression patterns and their functional implications in various biological contexts.
