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Two-stage testing procedures with independent filtering for genome-wide gene-environment interaction

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  • James Y. Dai
  • Charles Kooperberg
  • Michael Leblanc
  • Ross L. Prentice

Abstract

Several two-stage multiple testing procedures have been proposed to detect gene-environment interaction in genome-wide association studies. In this article, we elucidate general conditions that are required for validity and power of these procedures, and we propose extensions of two-stage procedures using the case-only estimator of gene-treatment interaction in randomized clinical trials. We develop a unified estimating equation approach to proving asymptotic independence between a filtering statistic and an interaction test statistic in a range of situations, including marginal association and interaction in a generalized linear model with a canonical link. We assess the performance of various two-stage procedures in simulations and in genetic studies from Women's Health Initiative clinical trials. Copyright 2012, Oxford University Press.

Suggested Citation

  • James Y. Dai & Charles Kooperberg & Michael Leblanc & Ross L. Prentice, 2012. "Two-stage testing procedures with independent filtering for genome-wide gene-environment interaction," Biometrika, Biometrika Trust, vol. 99(4), pages 929-944.
    • Handle: RePEc:oup:biomet:v:99:y:2012:i:4:p:929-944
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    File URL: http://hdl.handle.net/10.1093/biomet/ass044
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    Cited by:

    1. Noha Sharafeldin & Martha L. Slattery & Qi Liu & Conrado Franco-Villalobos & Bette J. Caan & John D. Potter & Yutaka Yasui, 2017. "Multiple Gene-Environment Interactions on the Angiogenesis Gene-Pathway Impact Rectal Cancer Risk and Survival," IJERPH, MDPI, vol. 14(10), pages 1-15, September.
    2. James Y. Dai & C. Jason Liang & Michael LeBlanc & Ross L. Prentice & Holly Janes, 2018. "Case†only approach to identifying markers predicting treatment effects on the relative risk scale," Biometrics, The International Biometric Society, vol. 74(2), pages 753-763, June.
    3. Jennifer A. Smith & Wei Zhao & Kalyn Yasutake & Carmella August & Scott M. Ratliff & Jessica D. Faul & Eric Boerwinkle & Aravinda Chakravarti & Ana V. Diez Roux & Yan Gao & Michael E. Griswold & Gerar, 2017. "Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies," IJERPH, MDPI, vol. 14(12), pages 1-18, December.
    4. Ariane Mbemi & Sunali Khanna & Sylvianne Njiki & Clement G. Yedjou & Paul B. Tchounwou, 2020. "Impact of Gene–Environment Interactions on Cancer Development," IJERPH, MDPI, vol. 17(21), pages 1-15, November.
    5. Thomas W Winkler & Anne E Justice & L Adrienne Cupples & Florian Kronenberg & Zoltán Kutalik & Iris M Heid & the GIANT consortium, 2017. "Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.

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