Quality control and data analysis of fecal metabolite detection
Principal component analysis (PCA) was performed on metabolite data, and
the OPLS-DA model was calculated using the R (3.3.2) package “ropls”
to visualize the clustering of samples (Thévenot et al., 2015). The
differential metabolites were screened by combining the fold difference,
P-value of the t -test, and VIP value of the OPLS-DA model. The
screening criteria were FC>1, P-value <0.05, and
VIP>1. The cluster profiler used the hypergeometric test
method to perform enrichment analysis on the annotation results of the
differential KEGG metabolites and screened some representative metabolic
pathways for impact value and significance as the enrichment criteria.