Additional file 1: Table S1. of Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines

Description of algorithms used in the analyses. Table S2. Concordance rate of different combination of algorithms with dataset without missing data. Table S3. Number of variants and their review statuses for which majority of algorithm assertion was opposite to that in ClinVar. Table S4. Concordance among different combination of algorithms. Note that as MetaSVM and MetaLR are very similar and uses the same training set we omitted combinations that included both of these algorithms. Table S5. Percentage of damaging/tolerant call by each algorithm. Table S6. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and a cutoff estimated from the ROC curve of the indicated datasets. (XLSX 1124 kb)本分析所用算法说明。表S2：无缺失数据数据集下不同算法组合的一致性率。表S3：多数算法断言与ClinVar记载不符的变异体数量及其审核状态。表S4：不同算法组合间的一致性水平。注：由于MetaSVM与MetaLR高度相似且采用相同训练集，本研究未纳入同时包含这两种算法的组合。表S5：各算法所生成的致病性（damaging）与良性（tolerant）预测调用占比。表S6：基于指定数据集的受试者工作特征（ROC）曲线估算得到的灵敏度、特异度、阳性预测值（Positive Predictive Value, PPV）、阴性预测值（Negative Predictive Value, NPV）以及截断值。（XLSX 格式，文件大小1124 KB）