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• W2516288093 abstract "ABSTRACT Whole exome and genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognised as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants. Here we present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets. Using the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, and identifies 43 variants previously reported as pathogenic that can now be reclassified. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset." @default.
• W2516288093 created "2016-09-16" @default.
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• W2516288093 date "2016-09-02" @default.
• W2516288093 modified "2023-10-18" @default.
• W2516288093 title "Using high-resolution variant frequencies to empower clinical genome interpretation" @default.
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• W2516288093 doi "https://doi.org/10.1101/073114" @default.
• W2516288093 hasPublicationYear "2016" @default.
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