Fig. 6

Evaluation of the performance of microbial markers in distinguishing among healthy subjects, patients with CD, and patients with UC using differentially abundant genera. (a) Optimal number of genus markers in a random forest model based on classification errors comparing healthy subjects and patients with IBD. (b) The importance of marker candidates evaluated in the training process of the random forest model in comparisons of healthy subjects and patients with IBD. (c) Classification ability of the random forest model trained with the two genera selected as markers in distinguishing between healthy subjects and patients with IBD. (d) Optimal number of genus markers in a random forest model based on classification errors comparing healthy subjects and patients with CD. (e) The importance of marker candidates evaluated in the training process of the random forest model in comparisons of healthy subjects and patients with CD. (f) Classification ability of the random forest model trained with the two genera selected as markers in distinguishing between healthy subjects and patients with CD. (g) Optimal number of genus markers in a random forest model based on classification errors comparing healthy subjects and patients with UC. (h) The importance of marker candidates evaluated in the training process of the random forest model in comparisons of healthy subjects and patients with UC. (i Classification ability of the random forest model trained with the three genera selected as markers in distinguishing between healthy subjects and patients with UC. (j) Optimal number of genus markers in a random forest model based on classification errors comparing patients with CD group and patients with UC. (k) The importance of marker candidates evaluated in the training process of the random forest model in comparisons of patients with CD and patients with UC. (l) Classification ability of the random forest model trained with the three genera selected as markers in distinguishing between patients with CD and patients with UC. (a, d, g, and j) The red arrows indicate the optimal number of genus markers in the random forest models. (b, e, h, and k) The genera marked with a star in the shaded area indicated by the red dotted line are the taxa contributing to the highest level of classification accuracy. The classification power of the random forest model trained by applying the optimal number of markers was evaluated by calculating AUROC. CD, Crohn’s disease; UC, ulcerative colitis; OOB Error, out-of-bag error; AUROC, Area Under the Receiver Operating Characteristic curve.