Meta-analysis of Gene-level Tests for Rare Variant Association

Overview

Journal Nat Genet

Specialty Genetics

Date 2013 Dec 17

PMID 24336170

Citations 125

Authors

Dajiang J Liu

Gina M Peloso

Xiaowei Zhan

Oddgeir L Holmen

Matthew Zawistowski

Shuang Feng

Majid Nikpay

Paul L Auer

Anuj Goel

He Zhang

Ulrike Peters

Martin Farrall

Marju Orho-Melander

Charles Kooperberg

Ruth McPherson

Hugh Watkins

Cristen J Willer

Kristian Hveem

Olle Melander

Sekar Kathiresan

Goncalo R Abecasis

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

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