Using high-resolution variant frequencies to empower clinical genome interpretation

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Title: Using high-resolution variant frequencies to empower clinical genome interpretation
Authors: Whiffin, N
Minikel, E
Walsh, R
O'Donnell-Luria, A
Karczewski, K
Ing, AY
Barton, PJR
Funke, B
Cook, SA
MacArthur, DG
Ware, JS
Item Type: Journal Article
Abstract: Purpose: 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. Methods: 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. Results: 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, without removing true pathogenic variants (false positive rate<0.001). Conclusion: We outline a statistically robust framework for assessing whether a variant is 'too common' to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.
Issue Date: 18-May-2017
Date of Acceptance: 2-Feb-2017
ISSN: 1530-0366
Publisher: Nature Publishing Group
Start Page: 1151
End Page: 1158
Journal / Book Title: Genetics in Medicine
Volume: 19
Copyright Statement: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit © The Author(s) 2017
Sponsor/Funder: Fondation Leducq
Wellcome Trust
Department of Health
Wellcome Trust
Funder's Grant Number: 11 CVD-01
Keywords: 0604 Genetics
1103 Clinical Sciences
Genetics & Heredity
Publication Status: Published online
Appears in Collections:National Heart and Lung Institute
Faculty of Medicine

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