Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment
Fig 2
Metabolome features cluster most significantly according to patient covariate groups.
A-D. Principal coordinate analysis (PCoA) of the Jaccard distance calculated from microbiome samples. The differences among the groups were tested for significance using a PERMANOVA on the distance matrices. E-L. For metabolome (E-H) and immunoproteome (I-L) features the principal component analysis (PCA) was performed on log-transformed and scaled features (zero mean and unit variance). The differences among groups were assessed using the multivariate analysis of variance (MANOVA) model for the first two principal components.