期刊
GENETIC EPIDEMIOLOGY
卷 32, 期 3, 页码 255-263出版社
WILEY
DOI: 10.1002/gepi.20300
关键词
epistasis; two-stage analyses
资金
- NATIONAL CANCER INSTITUTE [U01CA125489, R01CA074841, P01CA053996, R29CA074841] Funding Source: NIH RePORTER
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL074745] Funding Source: NIH RePORTER
- NCI NIH HHS [P01 CA053996, U01 CA125489, U01 CA125489-03, R29 CA074841, CA 74841, CA 53996, R01 CA074841-09, CA 125489, R01 CA074841, P01 CA053996-30] Funding Source: Medline
- NHLBI NIH HHS [HL 74745, R01 HL074745-03, R01 HL074745] Funding Source: Medline
In this paper we investigate the power to identify gene x gene interactions in genome-wide association studies. In our analysis we focus on two-stage analyses: analyses in which we only test for interactions between single nucleotide polymorphisms that show some marginal effect. We give two algorithms to compute significance levels for such an analyses. One involves a Bonferoni correction on the number of interactions that are actually tested, and one is a resampling procedure similar to the one proposed by [Lin (2006) Am. J. Hum. Genet. 78:505-509]. We also give an algorithm to carry out approximate power calculations for studies that plan to use a two-stage analysis. We find that for most plausible interaction effects a two-stage analysis can dramatically increase the power to identify interactions compared to a single-stage analysis based on simulation studies using known genetic models and data from existing genome-wide association studies.
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