csuWGCNA: a combination of signed and unsigned WGCNA to capture negative correlations

In original Weighted Gene Co-expression Network Analysis (WGCNA), the signed network considers the sign of correlation and only positive correlations make sense in the network. The unsigned network regard both highly positive and negative correlations as connected. This design results in loss of negative correlation in the signed network and moderate negative correlations in the unsigned network. To avoid these limitations, we provided a modified method of WGCNA named Combination of Signed and Unsigned WGCNA (csuWGCNA). We created networks for signed, unsigned and csuWGCNA on two gene expression datasets of the human brain from Stanley Medical Research Institute (SMRI) and BrainGVEX. The results obtained from our investigation indicate that our method is better than signed and unsigned WGCNA in capturing negatively correlated gene pairs. Especially for the relationship between miRNA, lncRNA and their target genes.