Weighted gene coexpression network analysis (WGCNA) with k-mean values was applied by Botía et al20 to transcriptomic data from GTEx and Braineac to generate coexpression modules.21,22 We assessed whether the candidate genes in this study were important in certain modules using the tool CoExpNets.23 The GTEx- and Braineac-derived networks were used to assign each candidate gene to a cell type, while the GTEx networks alone were used to assess the functional pathways associated with each gene. In brief, each module is associated with a cell type based on the enrichment of cell-type–specific genes within the module. The enrichment is assessed by using the Fisher exact test to evaluate whether we can find an overlap between the module genes and the brain cell–type markers that is more significant than random chance. Each gene of interest is then assigned to a primary cell type based on its module membership, which is the correlation of the expression of our gene of interest with the first principal component of each module. This correlation is always between 0 and 1; we use module membership as a measure of how reliable the assignment is of each gene to its module.
