Journal
NATURE GENETICS
Volume 46, Issue 2, Pages 200-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/ng.2852
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Categories
Funding
- National Human Genome Research Institute [R01HG007022]
- National Eye Institute [R01EY022005]
- National Heart, Lung, and Blood Institute [R01HL117626, T32HL007208]
- Massachusetts General Hospital (MGH)
- Howard Goodman Fellowship from MGH, the Donovan Family Foundation [R01HL107816]
- National Heart, Lung, and Blood Institute, US National Institutes of Health, US Department of Health and Human Services [N01WH22110, N01WH24152, N01WH32100-2, N01WH32105-6, N01WH32108-9, N01WH32111-13, N01WH32115, N01WH32118-32119, N01WH32122, N01WH42107-26, N01WH42129-32, N01WH44221]
- Canadian Institutes of Health Research (CIHR) [MOP-82810, MOP-77682, MOP-2380941]
- Canada Foundation for Innovation [11966]
- Swedish Research Council
- Swedish Heart and Lung Foundation
- Phlsson Foundation
- Novo Nordic Foundation and European Research Council [StG-282255]
- Novo Nordisk Fonden [NNF13OC0005339, NNF14OC0009819] Funding Source: researchfish
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The majority of reported complex disease associations for common genetic variants have been identified through metaanalysis, 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 individuallevel 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 similar to 18,500 individuals genotyped with exome arrays.
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