M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity

• Published in: Nature genetics Vol. 48; no. 12; pp. 1581 - 1586
• Main Authors: Jagadeesh, Karthik A, Wenger, Aaron M, Berger, Mark J, Guturu, Harendra, Stenson, Peter D, Cooper, David N, Bernstein, Jonathan A, Bejerano, Gill
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.12.2016; Nature Publishing Group
• Subjects: 45; 631/208/212/2166; 631/208/2489; 692/308/2056; 692/700/228/2050/1512; Agriculture; Amino acids; Animal Genetics and Genomics; Biomedicine; Cancer Research; Classification; Computational Biology - methods; Disease; Disease - genetics; DNA Mutational Analysis - methods; Exome - genetics; Gene Function; Genes; Genetic Markers - genetics; Genetic Predisposition to Disease; Genomes; Genomics; Human Genetics; Humans; Medical research; Mutation; Mutation - genetics; Pathogens; Predictive Value of Tests; Software; Teaching methods; technical-report
• ISSN: 1061-4036; 1546-1718; 1546-1718
• DOI: 10.1038/ng.3703

Gill Bejerano and colleagues present M-CAP, a classifier that estimates variant pathogenicity in clinical exome data sets. They show that M-CAP outperforms other existing methods at all thresholds and correctly dismisses 60% of rare missense variants of uncertain significance at 95% sensitivity. Variant pathogenicity classifiers such as SIFT, PolyPhen-2, CADD, and MetaLR assist in interpretation of the hundreds of rare, missense variants in the typical patient genome by deprioritizing some variants as likely benign. These widely used methods misclassify 26 to 38% of known pathogenic mutations, which could lead to missed diagnoses if the classifiers are trusted as definitive in a clinical setting. We developed M-CAP, a clinical pathogenicity classifier that outperforms existing methods at all thresholds and correctly dismisses 60% of rare, missense variants of uncertain significance in a typical genome at 95% sensitivity.