WGCNA is not a part of Qlucore Omics Explorer but you can achieve similar results with Qlucore by clustering the genes with hierarchical clustering and look for groups of similar genes "manually" with the exception of the techniques for calculating pair wise distances. Another way in Qlucore Omics Explorer to find correlated genes is of course to look in the PCA plot and work with the correlation tool.
WCGNA background
WGCNA is typically used to cluster genes and create so called "gene modules" consisting of genes with high correlation. Simply put, the steps are something like the following:
- Calculate all pair wise (absolute) correlations among genes
- Transform with a power transformation so that low correlations get even lower weight (instead of setting a hard threshold)
- Create a network where the genes are connected with edges with weights given by the transformed correlations. The exponent in the transformation is determined so that this network is approximately scale-free
- Calculate a dissimilarity between each pair of genes by looking at their "topological overlap", essentially how many "common neighbors" they have in the network
- Apply hierarchical clustering to this dissimilarity matrix
- Use a "dynamic tree cut" algorithm to cut the dendrogram into clusters, or modules |
