Missense variant pathogenicity predictors generalize well across a range of function-specific prediction challenges

Human Mutation
Vikas PejaverPredrag Radivojac

Abstract

The steady advances in machine learning and accumulation of biomedical data have contributed to the development of numerous computational models that assess the impact of missense variants. Different methods, however, operationalize impact differently. Two common tasks in this context are the prediction of the pathogenicity of variants and the prediction of their effects on a protein's function. These are related but distinct problems, and it is unclear whether methods developed for one are optimized for the other. The Critical Assessment of Genome Interpretation (CAGI) experiment provides a means to address this question empirically. To this end, we participated in various protein-specific challenges in CAGI with two objectives in mind. First, to compare the performance of methods in the MutPred family with the state-of-the-art. Second and more importantly, to investigate the applicability of general-purpose pathogenicity predictors to the classification of specific function-altering variants without additional training or calibration. We find that our pathogenicity predictors performed competitively with other methods, outputting score distributions in agreement with experimental outcomes. Overall, we conclude that binary cla...Continue Reading

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Citations

Apr 20, 2019·Pigment Cell & Melanoma Research·Christopher LiDouglas Grossman
Jun 12, 2019·Human Mutation·Vikas PejaverYana Bromberg
Jun 12, 2019·Human Mutation·Angélique QuartierAmélie Piton
Sep 10, 2019·Pediatric Dermatology·Alain K TranChristopher Barnett
Dec 17, 2019·The Journal of Clinical Endocrinology and Metabolism·Miguel Vázquez-MorenoDavid Meyre
Sep 2, 2020·Molecular Genetics & Genomic Medicine·Alejandro García-CastañoFelix Claverie-Martin
Aug 18, 2017·Human Mutation·Roger A HoskinsSteven E Brenner
Dec 29, 2020·The Journal of Biological Chemistry·Aleksandr V PopovDmitry O Zharkov
Oct 28, 2020·Proceedings of the National Academy of Sciences of the United States of America·Sumaiya IqbalDennis Lal
Nov 4, 2020·Intractable & Rare Diseases Research·Ana Perdomo-RamirezFelix Claverie-Martin

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