Journal article
A Protocol for Weighted Gene Co-expression Network Analysis With Module Preservation and Functional Enrichment Analysis for Tumor and Normal Transcriptomic Data
Bio-protocol, Vol.15(18), e5447
2025
DOI: 10.21769/BioProtoc.5447
PMCID: PMC12457846
PMID: 41000162
Abstract
Weighted gene co-expression network analysis (WGCNA) is widely used in transcriptomic studies to identify groups of highly correlated genes, aiding in the understanding of disease mechanisms. Although numerous protocols exist for constructing WGCNA networks from gene expression data, many focus on single datasets and do not address how to compare module stability across conditions. Here, we present a protocol for constructing and comparing WGCNA modules in paired tumor and normal datasets, enabling the identification of modules involved in both core biological processes and those specifically related to cancer pathogenesis. By incorporating module preservation analysis, this approach allows researchers to gain deeper insights into the molecular underpinnings of oral cancer, as well as other diseases. Overall, this protocol provides a framework for module preservation analysis in paired datasets, enabling researchers to identify which gene co-expression modules are conserved or disrupted between conditions, thereby advancing our understanding of disease-specific vs. universal biological processes.
Details
- Title: Subtitle
- A Protocol for Weighted Gene Co-expression Network Analysis With Module Preservation and Functional Enrichment Analysis for Tumor and Normal Transcriptomic Data
- Creators
- Phuong Nguyen - University of IowaErliang Zeng - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Bio-protocol, Vol.15(18), e5447
- DOI
- 10.21769/BioProtoc.5447
- PMID
- 41000162
- PMCID
- PMC12457846
- NLM abbreviation
- Bio Protoc
- ISSN
- 2331-8325
- eISSN
- 2331-8325
- Language
- English
- Date published
- 2025
- Academic Unit
- Preventive and Community Dentistry; Iowa Neuroscience Institute; Biostatistics; Dental Research
- Record Identifier
- 9984962537702771
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