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. 2020 Oct 13;23(1):69–79. doi: 10.1038/s41436-020-00972-3

Table 1.

CardioBoost outperforms existing genome-wide tools for the classification of holdout test variants.

% Cardiomyopathies Arrhythmias
CardioBoost M-CAP REVEL CardioBoost M-CAP REVEL
Overall accuracy 63.3a 28.4 17.4 81.2a 30.5 37
Proportion of variants classified with high confidence 70.2a 33.9 22 88.3a 33.8 40.3
Accuracy of high-confidence classifications 90.2 83.8 79.2 91.9 90.4 91.9
Proportion of variants with indeterminate classification 29.8a 66.1 78 11.7a 66.2 59.7
 TPR 69.5a 41.5 28 83.3a 48.8 65.5
 PPV 86.3 81.7 76.7 90.9 91.1 91.7
 TNR 56a 13 5 78.6a 8.6 2.9
 NPV 96.6 92.9 100 93.2 85.7 100

The performance of each tool is reported using the clinically relevant variant classification thresholds: high-confidence disease-causing (Pr ≥ 0.9), high-confidence benign (Pr ≤ 0.1), and indeterminate. For each predictive performance measure (see Supplementary Methods for details) the best algorithm is highlighted in bold. Permutation tests were performed to evaluate whether the performance of CardioBoost was significantly different from the best value obtained by M-CAP or REVEL.

NPV negative predictive value, PPV positive predictive value, TNR true negative rate, TPR true positive rate.

aP value ≤ 0.001.