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PurposeWhere multiple in silico tools are concordant, the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) framework affords supporting evidence toward pathogenicity or benignity, equivalent to a likelihood ratio of ~2. However, limited availability of "clinical truth sets" and prior use in tool training limits their utility for evaluation of tool performance.MethodsWe created a truth set of 9,436 missense variants classified as deleterious or tolerated in clinically validated high-throughput functional assays for BRCA1, BRCA2, MSH2, PTEN, and TP53 to evaluate predictive performance for 44 recommended/commonly used in silico tools.ResultsOver two-thirds of the tool-threshold combinations examined had specificity of <50%, thus substantially overcalling deleteriousness. REVEL scores of 0.8-1.0 had a Positive Likelihood Ratio (PLR) of 6.74 (5.24-8.82) compared to scores <0.7 and scores of 0-0.4 had a Negative Likelihood Ratio (NLR) of 34.3 (31.5-37.3) compared to scores of >0.7. For Meta-SNP, the equivalent PLR = 42.9 (14.4-406) and NLR = 19.4 (15.6-24.9).ConclusionAgainst these clinically validated "functional truth sets," there was wide variation in the predictive performance of commonly used in silico tools. Overall, REVEL and Meta-SNP had best balanced accuracy and might potentially be used at stronger evidence weighting than current ACMG/AMP prescription, in particular for predictions of benignity.

Original publication

DOI

10.1038/s41436-021-01265-z

Type

Journal article

Journal

Genetics in medicine : official journal of the American College of Medical Genetics

Publication Date

11/2021

Volume

23

Pages

2096 - 2104

Addresses

Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.

Keywords

Humans, Neoplasms, Genomics, Mutation, Missense, Computer Simulation, Genetic Variation