Introduction

What is WGCNA?

Weighted Gene Correlation Network Analysis (WGCNA) is a widely used data mining and analysis method developed to study biological networks based on pairwise correlations between variables.

This method was first published by B. Zhang and S. Horvath (A general framework for weighted gene co-expression network analysis, Statistical applications in genetics and molecular biology, 4 (1), 2005).

Although mainly used to analyse gene expression data, WGCNA is suited to analyse any type of continuous biological omics data. The rationale behind this method is to use the correlations levels between the omics features to extract meaningful results, complementing the traditional methods of omics data analysis who focus on statistically relevant differences of expression and/or abundance of the omics features between groups.

What does this application do?

This application allows users with little or no coding skills to try, explore and play with the WGCNA method. In order to make this experience as straightforward as possible, we have restricted the data available in this application to two model datasets of gene expression in mice. Other implementations of this method within the eTRIKS project will allow users to upload their own data.

In general terms, this application will let the user: