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.