Meta-analysis of gene-level tests for rare variant association. Nat Genet 2014 Feb;46(2):200-4
Date
12/18/2013Pubmed ID
24336170Pubmed Central ID
PMC3939031DOI
10.1038/ng.2852Scopus ID
2-s2.0-84895808047 (requires institutional sign-in at Scopus site) 139 CitationsAbstract
The majority of reported complex disease associations for common genetic variants have been identified through meta-analysis, a powerful approach that enables the use of large sample sizes while protecting against common artifacts due to population structure and repeated small-sample analyses sharing individual-level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the focus of analysis. Here we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable-threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features from single-variant meta-analysis approaches and demonstrate its use in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays.
Author List
Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GRAuthor
Paul L. Auer PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Data Interpretation, StatisticalExome
Genetic Association Studies
Genetic Variation
Genetics, Population
Genotype
Humans
Lipids
Meta-Analysis as Topic
Models, Genetic
Monte Carlo Method
Research Design
