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Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction

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  • Arend Voorman
  • Thomas Lumley
  • Barbara McKnight
  • Kenneth Rice

Abstract

Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in GE work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in GE GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in GE GWAS can alleviate this problem.

Suggested Citation

  • Arend Voorman & Thomas Lumley & Barbara McKnight & Kenneth Rice, 2011. "Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-7, May.
  • Handle: RePEc:plo:pone00:0019416
    DOI: 10.1371/journal.pone.0019416
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    1. Ilja M Nolte & Chris Wallace & Stephen J Newhouse & Daryl Waggott & Jingyuan Fu & Nicole Soranzo & Rhian Gwilliam & Panos Deloukas & Irina Savelieva & Dongling Zheng & Chrysoula Dalageorgou & Martin F, 2009. "Common Genetic Variation Near the Phospholamban Gene Is Associated with Cardiac Repolarisation: Meta-Analysis of Three Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-10, July.
    2. B. Devlin & Kathryn Roeder, 1999. "Genomic Control for Association Studies," Biometrics, The International Biometric Society, vol. 55(4), pages 997-1004, December.
    3. Feng Zhang & Yuping Wang & Hong-Wen Deng, 2008. "Comparison of Population-Based Association Study Methods Correcting for Population Stratification," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-7, October.
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    1. Rajita Menon & Vivek Ramanan & Kirill S Korolev, 2018. "Interactions between species introduce spurious associations in microbiome studies," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-20, January.
    2. Zihuai He & Min Zhang & Seunggeun Lee & Jennifer A. Smith & Sharon L. R. Kardia & V. Diez Roux & Bhramar Mukherjee, 2017. "Set-Based Tests for the Gene–Environment Interaction in Longitudinal Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 966-978, July.
    3. Jennifer E Huffman & Eva Albrecht & Alexander Teumer & Massimo Mangino & Karen Kapur & Toby Johnson & Zoltán Kutalik & Nicola Pirastu & Giorgio Pistis & Lorna M Lopez & Toomas Haller & Perttu Salo & A, 2015. "Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    4. Wei Zhao & Erin B. Ware & Zihuai He & Sharon L. R. Kardia & Jessica D. Faul & Jennifer A. Smith, 2017. "Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting," IJERPH, MDPI, vol. 14(10), pages 1-17, September.

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