Estimation of the multiple testing burden for genomewide association studies of nearly all common variants.
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.
Pe'er
Itsik
I
Department of Computer Science, Columbia University, New York, New York, USA.
Yelensky
Roman
R
Altshuler
David
D
Daly
Mark J
MJ
D001699:Biometry; D044383:Black People / Q000235:genetics; D030541:Databases, Genetic; D004812:Epidemiologic Methods; D005821:Genetic Techniques / Q000706:statistics & numerical data*; D014644:Genetic Variation; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D044465:White People / Q000235:genetics