Year: 2013
Type: review
Abstract: The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large samples sizes while protecting against common artifacts due to population structure, repeated small sample analyses, and/or limitations with sharing individual level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the unit of analysis. Here, we propose and evaluate new approaches for meta-analysis of rare variant association. We show that our approach retains useful features of single variant meta-analytic approaches and demonstrate its utility in a study of blood lipid levels in ~18,500 individuals genotyped with exome arrays.
Source: arXiv (Cornell University)
Authors: Liu, Dajiang J., Peloso, Gina M., Zhan, Xiaowei, Holmen, Oddgeir, Zawistowski, Matthew, Feng, Shuang, Nikpay, Majid, Auer, Paul L., Goel, Anuj, Zhang, He, Peters, Ulrike, Farrall, Martin, Orho-Melander, Marju, Kooperberg, Charles, McPherson, Ruth, Watkins, Hugh, Willer, Cristen J., Hveem, Kristian, Melander, Olle, Kathiresan, Sekar, Abecasis, Gonçalo R.
Institutions: University of Michigan, Broad Institute, Massachusetts General Hospital, Norwegian University of Science and Technology, Fred Hutch Cancer Center, Centre for Human Genetics, University of Oxford, Michigan Medicine, University of Washington, Malmö University, Lund University, Ottawa Heart Institute, National Institutes of Health, National Heart, Lung, and Blood Institute
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W1819969402