WGCNA Web Tool

The WGCNA Web Tool provides a server-based workflow to derive modular structure from bulk gene expression data. It accepts a gene expression matrix with genes as rows and samples as columns, optionally aligned phenotype annotations. It focuses on identifying co-expression modules, computing module eigengenes, and assessing associations with traits to reveal biologically meaningful patterns. The audience includes molecular biologists, genomic researchers, and data scientists seeking reproducible module-based insights without coding custom pipelines.
Domain logic and features include a reproducible pipeline that constructs a weighted adjacency matrix using a user-specified soft-threshold power, derives a topological overlap matrix (TOM), performs hierarchical clustering, and applies dynamic tree cutting to define modules. Optional steps include merging adjacent modules, choosing signed or unsigned networks, and evaluating cross-dataset preservation. Advanced users can adjust thresholds, perform sensitivity analyses, or export gene lists and hub genes.
Outputs comprise per-module gene lists, module eigengenes, trait correlations, module-trait p-values, hub gene candidates, and exportable CSV/JSON files for downstream analysis. The tool emphasizes reproducibility with fixed seeds, parameter logging, and an audit trail. It supports large datasets via scalable processing and streaming where feasible. In practice, researchers use this to compare network architectures across conditions, identify biologically coherent modules, and prioritize hub genes for experimental validation.
Overall, the WGCNA Web Tool accelerates module discovery, trait association interpretation, and cross-study comparisons without the need to write bespoke analysis pipelines.