TY - JOUR T1 - Using high-resolution variant frequencies to empower clinical genome interpretation JF - bioRxiv DO - 10.1101/073114 SP - 073114 AU - Nicola Whiffin AU - Eric Minikel AU - Roddy Walsh AU - Anne O’Donnell-Luria AU - Konrad Karczewski AU - Alexander Y Ing AU - Paul JR Barton AU - Birgit Funke AU - Stuart A Cook AU - Daniel MacArthur AU - James S Ware Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/11/02/073114.abstract N2 - 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. ER -