Fig. 3

X-CAP outperforms competitors. a For each model, we plot the ROC curve and associated AUROC metric on the test set of \(\mathcal {D}_{\text {original}}\). X-CAP has the highest AUROC, improving upon the previous state-of-the-art by 0.14 absolute points. The orange and green dotted lines display X-CAP’s performance when trained only on variants present in the databases used by MutPred-LoF and ALoFT, respectively. To ensure a fair comparison, we randomly subsampled these datasets to the size used in the original papers (n indicates the size of the training set). b We enlarge the portion of the plot above the dashed line in panel a to show performance in the clinically relevant, high-sensitivity region (TPR ≥0.95). We also display the hsr-AUROC, which is the normalized area under the curve in the high-sensitivity region. We optimized X-CAP to excel in this region, rather than over the full ROC. At 95% sensitivity, X-CAP correctly classifies 80.0% of benign stopgain variants, over four times more than any other classifier