Predicting phenotype from genotype: Improving accuracy through more robust experimental and computational modeling.

ABSTRACT: Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predicti

SUBMITTER: Gallion J 

PROVIDER: S-EPMC5516182 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature