%0 Generic %A Ghosh, Rajarshi %A Oak, Ninad %A Plon, Sharon %D 2017 %T Additional file 1: Table S1. of Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines %U https://springernature.figshare.com/articles/dataset/Additional_file_1_Table_S1_of_Evaluation_of_in_silico_algorithms_for_use_with_ACMG_AMP_clinical_variant_interpretation_guidelines/5639572 %R 10.6084/m9.figshare.5639572.v1 %2 https://springernature.figshare.com/ndownloader/files/9825952 %K Variant interpretation %K In silico algorithm %K ROC %K ClinVar %K ACMG %K Clinical genetics %K Diagnostics %X 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) %I figshare