Fig. 9

Performance of MIOSTONE in host’s disease status prediction in terms of AUROC. The evaluation was performed on three simulated and seven real microbiome datasets. MIOSTONE is compared against nine baseline methods, divided into two categories: tree-agnostic methods and tree-aware methods. Each model was trained by times using different train-test splits, and reported by the average performance along with 95% confidence intervals. The models’ performances are measured by the area under the receiver operating characteristic curve (AUROC). For scientific rigor, the performance comparison between MIOSTONE and any other baseline method is quantified using one-tailed two-sample t-tests to calculate p-values: \(****\ p\text {-value}\le 0.0001\); \(***\ p\text {-value}\le 0.001\); \(**\ p\text {-value}\le 0.01\); \(*:\ p\text {-value}\le 0.05\); \(\text {ns}:\ p\text {-value}> 0.05\)