Fig. 2

Weighted co-correlation network analysis of microbial and human proteins. The weighted correlation network analysis (WGCNA) R package was used to build a microbial-host functional weighted co-correlation network using intensity-based absolute quantification (iBAQ) values. a Correlations between proteins and modules are shown by the heatmap, with positive correlations shown in red and negative correlations shown in blue. Row sidebars represent the top taxa and biological processes assigned to each of the proteins (no separate correlation coefficients were calculated for taxa and biological processes). b The protein dendrogram and module assignment are displayed, with five modules identified using dynamic tree cut. c Spearman’s rank correlation was used to determine correlation coefficients between individual cytokines/chemokines and module eigengenes (the first principal component of the expression matrix of the corresponding module) for all samples. Finally, we reported the average Spearman’s correlation coefficients for all pro-inflammatory cytokines and chemokines. d Similarly, Spearman’s correlation coefficients were calculated between module eigengenes and Nugent scores [bacterial vaginosis (BV)] and sexually transmitted infections (STIs) as a categorical variable