Estimation of the multiple testing burden for genomewide association studies of nearly all common variants
- 17 March 2008
- journal article
- research article
- Published by Wiley in Genetic Epidemiology
- Vol. 32 (4), 381-385
- https://doi.org/10.1002/gepi.20303
Abstract
Genomewide association studies are an exciting strategy in genetics, recently becoming feasible and harvesting many novel genes linked to multiple phenotypes. Determining the significance of results in the face of testing a genomewide set of multiple hypotheses, most of which are producing noisy, null‐distributed association signals, presents a challenge to the wide community of association researchers. Rather than each study engaging in independent evaluation of significance standards, we have undertaken the task of developing such standards for genomewide significance, based on data collected by the International Haplotype Map Consortium. We report an estimated testing burden of a million independent tests genomewide in Europeans, and twice that number in Africans. We further identify the sensitivity of the testing burden to the required significance level, with implications to staged design of association studies. Genet. Epidemiol. 2008.This publication has 23 references indexed in Scilit:
- Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot projectNature, 2007
- Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controlsNature, 2007
- A Note on Permutation Tests in Multistage Association ScansAmerican Journal of Human Genetics, 2006
- A common genetic variant in the NOS1 regulator NOS1AP modulates cardiac repolarizationNature Genetics, 2006
- Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studiesNature Genetics, 2006
- A haplotype map of the human genomeNature, 2005
- Efficiency and power in genetic association studiesNature Genetics, 2005
- Complement Factor H Polymorphism in Age-Related Macular DegenerationScience, 2005
- The International HapMap ProjectNature, 2003
- Genetic dissection of complex traits: guidelines for interpreting and reporting linkage resultsNature Genetics, 1995