Journal
ANNALS OF HUMAN GENETICS
Volume 75, Issue -, Pages 36-45Publisher
WILEY-BLACKWELL PUBLISHING, INC
DOI: 10.1111/j.1469-1809.2010.00572.x
Keywords
Interaction testing; parametric bootstrap; permutation methods
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Funding
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL074745] Funding Source: NIH RePORTER
- NHLBI NIH HHS [R01 HL074745, R01 HL074745-04] Funding Source: Medline
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P>Permutation tests are widely used in genomic research as a straightforward way to obtain reliable statistical inference without making strong distributional assumptions. However, in this paper we show that in genetic association studies it is not typically possible to construct exact permutation tests of gene-gene or gene-environment interaction hypotheses. We describe an alternative to the permutation approach in testing for interaction, a parametric bootstrap approach. Using simulations, we compare the finite-sample properties of a few often-used permutation tests and the parametric bootstrap. We consider interactions of an exposure with single and multiple polymorphisms. Finally, we address when permutation tests of interaction will be approximately valid in large samples for specific test statistics.
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