Fig. 2

Improvement of sample classification based on the integration of microbiota- and metabolite-based PLS-DA models. a Sample classifications are shown as provided by the microbial genus abundance-based PLS-DA model (top row), metabolite-based PLS-DA model (middle row), and combined Bayesian model (bottom row). Each column represents a unique sample from IBS and healthy sets as shown. Each square is colored according to the group assignment confidence based on the gradient as shown in the legend. Average assignment accuracy and confidence for each model are indicated at the right of the figure. b Application of the Bayesian integration model to a set of four new IBS-D samples. c Density distribution plots of PDI values for IBS-D and healthy adolescent samples. Top three discriminating genera and metabolites were used to compute PDI values. The X axis shows the range of PDI values; the Y axis represents the density (frequency) of PDI values at each position along the X axis. PDI values for individual kIBS and kHLT samples are shown on the plots as discrete points. Blue points represent new IBS-D samples. d Receiver operating characteristic analysis of PLS-DA models (left panel) and patient discrimination indices (right panel). AUC area under the curve (represents the discrimination ability of each model; higher value equals better discrimination), G genus, M metabolite