Weighted Gene Co-expression Network Analysis (WGCNA) & Hub Gene Discovery
Unravel complex systemic biological mechanisms by identifying highly correlated gene modules and crucial hub genes driving your phenotypic traits. Dawn of Bioinformatics Ltd. applies WGCNA-based methodologies to transform high-dimensional transcriptomic data into biologically meaningful networks.
Our workflows enable the detection of co-expression modules, correlation of modules with clinical or experimental traits, and identification of central hub genes using topological and connectivity-based metrics. This approach provides a deeper understanding of gene regulation, functional pathways, and disease mechanisms that support advanced research in systems biology and precision medicine.
Overview
Dawn of Bioinformatics Ltd. delivers advanced Weighted Gene Co-expression Network Analysis (WGCNA) and hub gene discovery services to uncover complex gene–gene interaction patterns and regulatory networks underlying biological systems. Our DawniLab experts construct robust co-expression networks to identify highly correlated gene modules and key hub genes associated with specific phenotypes, clinical traits, or disease conditions. By integrating statistical modeling with network-based approaches, we provide systems-level insights that support biomarker discovery and target prioritization.
Key Features
• Integration with differential expression and transcriptomics analysis.
• Construction of weighted gene co-expression networks.
• Identification of gene modules based on expression similarity.
• Module–trait relationship analysis (clinical or phenotypic correlation).
• Hub gene identification using topological metrics.
• Functional enrichment analysis of key modules.
• Network visualization and module exploration.
• Identification of potential biomarkers and therapeutic targets,
• Publication-ready figures (network plots, module–trait heatmaps, dendrograms).
Demo & Results
More Transcriptomics
- Bulk RNA-Sequencing & Differential Gene Expression (DGE) Analysis
- Single-Cell RNA-Seq (scRNA-Seq) Data Analysis
- Spatial Differential Gene Expression Analysis
- Weighted Gene Co-expression Network Analysis (WGCNA) & Hub Gene Discovery
- Non-Coding RNA Regulatory Network Analysis
- Time-Series Transcriptomics & Clinical Biomarker Profiling