WGCNA Analysis for Identifying Gene Modules in Ischemic Heart Failure

To investigate gene modules with relatedness in addition to obtaining differential genes using the limma package, we utilized the WGCNA package. By applying the goodSamplesGenes function with a filtering criterion of 0.5, we removed ineligible genes and samples to create a scale-free co-expression network. Subsequently, we calculated adjacency using β = 30 and scale-free R2 = 0.9 as a soft threshold, and converted it into a topological overlap matrix (TOM) to determine gene ratios and dissimilarity. To group genes with the same expression profile into gene modules, we employed average linkage hierarchical clustering, setting the minimum module size to 200 to ensure larger modules. Finally, we assessed the similarity of the modules' signature genes, selected cut lines of the module dendrogram to combine several modules for the next stage of the study, and completed the visualization of the signature gene network. Our use of WGCNA analysis effectively identified important modules in ischemic heart failure.