Fig 5.

A Average classification performance (accuracy) of three distinct classifiers (rf = Random Forest, pda = Pennalised Discriminant Analysis and glmnet = Lasso and Elastic-Net Regularized Generalized Linear Model) on data from targeted analysis. The performance was measured with cross-validation algorithm over 5 folds and 5 repetitions. Average performance reaches 70%–75%, which suggests that metabolites are indeed capable of distinguishing between cases and controls. B Top 20 most important metabolites used by RandomForest classifier. Metabolites identified as significantly different in targeted analysis are highlighted. We can see that indeed almost all metabolites (except for C2…C0) identified as significantly different are in the top of the list.