Estimation of the multiple testing burden for genomewide association studies of nearly all common variants

Authors

  • Itsik Pe'er,

    1. Department of Computer Science, Columbia University, New York
    Search for more papers by this author
  • Roman Yelensky,

    1. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
    2. Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts
    3. Harvard-M.I.T. Division of Health Sciences and Technology, Cambridge, Massachusetts
    Search for more papers by this author
  • David Altshuler,

    1. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
    2. Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts
    3. Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
    4. Broad Institute of M.I.T. and Harvard, Cambridge, Massachusetts
    5. Department of Genetics, Harvard Medical School, Boston, Massachusetts
    Search for more papers by this author
  • Mark J. Daly

    Corresponding author
    1. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
    2. Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
    3. Department of Medicine, Harvard Medical School, Boston, Massachusetts
    • Massachusetts General Hospital, 185 Cambridge Street, CPZN-6818, Boston, MA 02114-2790
    Search for more papers by this author

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. © 2008 Wiley-Liss, Inc.

Ancillary