We are glad to invite you to our next free webinar, Unlocking Complex Gene Networks with WGCNA, on Wednesday, 18 November 2026. The session covers Weighted Gene Co-expression Network Analysis (WGCNA) from the core theory to a complete, hands-on analysis of a real transcriptomics dataset in OmicsBox.
Differential expression tells you which genes change between conditions. WGCNA asks a different question: which genes behave together across all samples? Groups of co-expressed genes, called modules, often point to shared regulation and shared biological function. That makes WGCNA a strong method for finding regulatory networks and candidate genes, especially in studies with many samples or several traits.
Two sessions, same content
To fit different time zones, we run the webinar twice. Both sessions are free and have the same content.
- 9:30 CET: Register for the morning session
- 18:30 CET: Register for the evening session
What the WGCNA webinar covers
The session starts with a step-by-step introduction to the principles behind the algorithm. Marta explains how a co-expression network is built from expression data and how genes are grouped into modules. She also points out the parameters and decision points that matter most, so the results are robust and easy to interpret.
After a short introduction to OmicsBox, the webinar moves to a practical use case with a real transcriptomics dataset. The demo shows the full workflow, from the expression matrix to co-expression modules, and then on to functional enrichment of those modules. This last step links abstract gene clusters to biological processes and metabolic pathways.
What you will learn
- The core concepts of Weighted Gene Co-expression Network Analysis
- How to choose parameters, such as the soft-thresholding power, to build meaningful modules
- How to run a complete WGCNA workflow in the OmicsBox graphical interface, without writing code
- How to run functional enrichment on co-expression modules and interpret the results
Speakers
Marta Benegas is a Senior Bioinformatician at BioBam. She works on the transcriptomics and functional analysis tools in OmicsBox and has written our guide to WGCNA in OmicsBox.
Dr. Stefan Götz, CEO of BioBam, hosts the session and moderates the Q&A.
Who should join
The webinar is for researchers who work with RNA-seq or other expression data and want to go beyond lists of differentially expressed genes. It suits both newcomers to network analysis and users who already know WGCNA from R and want a faster, code-free workflow. There is time for questions at the end.
Before the webinar
If you want some background first, read our blog post Understanding WGCNA: Gene Co-Expression Analysis Made Easy in OmicsBox. To interpret your own modules, the Combined Pathway Analysis in OmicsBox 4.1 now includes WikiPathways next to Reactome and Plant Reactome.
To follow along with your own data later, you can start a free OmicsBox trial.
The method itself is described in: Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559. doi:10.1186/1471-2105-9-559
We look forward to seeing you on 18 November!
