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Estimation of the multiple testing burden for genomewide association studies of nearly all common variants
Author(s) -
Pe'er Itsik,
Yelensky Roman,
Altshuler David,
Daly Mark J.
Publication year - 2008
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20303
Subject(s) - multiple comparisons problem , genetic association , null hypothesis , statistical hypothesis testing , biology , computational biology , genetics , association (psychology) , association mapping , genome wide association study , false discovery rate , association test , statistics , gene , single nucleotide polymorphism , genotype , psychology , mathematics , psychotherapist
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. © 2008 Wiley‐Liss, Inc.