Performance estimates for other state-of-the-art models and phenotypic multi-task multi-kernel learning (MKL).

For internal validation, each model was assessed by nested k-fold cross-validation. For external validation on a set of novel missense variants, the web-based tools for the Gradient boosting and decision rule method were used (see ‘Validation’). Note that AU-PRC and AU-ROC are not available for the decision rule as it is not a probabilistic classifier. Phenotypic learning outperforms other models across all metrics and is shown in bold. Abbreviations: ACC–accuracy; AU-PRC–area under the precision recall curve; AU-ROC–area under the receiver operator characteristics curve.