IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0019416.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0019416
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0019416&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0019416?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. B. Devlin & Kathryn Roeder, 1999. "Genomic Control for Association Studies," Biometrics, The International Biometric Society, vol. 55(4), pages 997-1004, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marie-Claude Babron & Marie de Tayrac & Douglas N Rutledge & Eleftheria Zeggini & Emmanuelle Génin, 2012. "Rare and Low Frequency Variant Stratification in the UK Population: Description and Impact on Association Tests," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-9, October.
    2. Lei Zhang & Yu-Fang Pei & Jian Li & Christopher J Papasian & Hong-Wen Deng, 2009. "Univariate/Multivariate Genome-Wide Association Scans Using Data from Families and Unrelated Samples," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-12, August.
    3. Dominic Holland & Oleksandr Frei & Rahul Desikan & Chun-Chieh Fan & Alexey A Shadrin & Olav B Smeland & V S Sundar & Paul Thompson & Ole A Andreassen & Anders M Dale, 2020. "Beyond SNP heritability: Polygenicity and discoverability of phenotypes estimated with a univariate Gaussian mixture model," PLOS Genetics, Public Library of Science, vol. 16(5), pages 1-30, May.
    4. Vincent Michaud & Eulalie Lasseaux & David J. Green & Dave T. Gerrard & Claudio Plaisant & Tomas Fitzgerald & Ewan Birney & Benoît Arveiler & Graeme C. Black & Panagiotis I. Sergouniotis, 2022. "The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    5. Natalie DeForest & Yuqi Wang & Zhiyi Zhu & Jacqueline S. Dron & Ryan Koesterer & Pradeep Natarajan & Jason Flannick & Tiffany Amariuta & Gina M. Peloso & Amit R. Majithia, 2024. "Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    6. Parsa Akbari & Dragana Vuckovic & Luca Stefanucci & Tao Jiang & Kousik Kundu & Roman Kreuzhuber & Erik L. Bao & Janine H. Collins & Kate Downes & Luigi Grassi & Jose A. Guerrero & Stephen Kaptoge & Ju, 2023. "A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    7. Gang Zheng & Zhaohai Li & Mitchell H. Gail & Joseph L. Gastwirth, 2010. "Impact of Population Substructure on Trend Tests for Genetic Case–Control Association Studies," Biometrics, The International Biometric Society, vol. 66(1), pages 196-204, March.
    8. Sandosh Padmanabhan & Olle Melander & Toby Johnson & Anna Maria Di Blasio & Wai K Lee & Davide Gentilini & Claire E Hastie & Cristina Menni & Maria Cristina Monti & Christian Delles & Stewart Laing & , 2010. "Genome-Wide Association Study of Blood Pressure Extremes Identifies Variant near UMOD Associated with Hypertension," PLOS Genetics, Public Library of Science, vol. 6(10), pages 1-11, October.
    9. Jakris Eu-ahsunthornwattana & E Nancy Miller & Michaela Fakiola & Wellcome Trust Case Control Consortium 2 & Selma M B Jeronimo & Jenefer M Blackwell & Heather J Cordell, 2014. "Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data," PLOS Genetics, Public Library of Science, vol. 10(7), pages 1-20, July.
    10. Jianzhong Ma & Christopher I Amos, 2010. "Theoretical Formulation of Principal Components Analysis to Detect and Correct for Population Stratification," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-14, September.
    11. Claire L Simpson & Robert Wojciechowski & Konrad Oexle & Federico Murgia & Laura Portas & Xiaohui Li & Virginie J M Verhoeven & Veronique Vitart & Maria Schache & S Mohsen Hosseini & Pirro G Hysi & Le, 2014. "Genome-Wide Meta-Analysis of Myopia and Hyperopia Provides Evidence for Replication of 11 Loci," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-19, September.
    12. Matthieu Bouaziz & Christophe Ambroise & Mickael Guedj, 2011. "Accounting for Population Stratification in Practice: A Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-13, December.
    13. Aditi Shendre & Howard W Wiener & Marguerite R Irvin & Bradley E Aouizerat & Edgar T Overton & Jason Lazar & Chenglong Liu & Howard N Hodis & Nita A Limdi & Kathleen M Weber & Stephen J Gange & Degui , 2017. "Genome-wide admixture and association study of subclinical atherosclerosis in the Women’s Interagency HIV Study (WIHS)," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-23, December.
    14. Li Shaoyu & Lu Qing & Fu Wenjiang & Romero Roberto & Cui Yuehua, 2009. "A Regularized Regression Approach for Dissecting Genetic Conflicts that Increase Disease Risk in Pregnancy," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-30, October.
    15. Warrington Nicole M. & Tilling Kate & Howe Laura D. & Paternoster Lavinia & Pennell Craig E. & Wu Yan Yan & Briollais Laurent, 2014. "Robustness of the linear mixed effects model to error distribution assumptions and the consequences for genome-wide association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(5), pages 567-587, October.
    16. Wang, Linglu & Li, Qizhai & Li, Zhaohai & Zheng, Gang, 2011. "Bayes factors in the presence of population stratification," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 836-841, July.
    17. Boitard Simon & Mangin Brigitte & Azaïs Jean-Marc, 2010. "Asymptotic Distribution of the "Orthogonal" Quantitative Transmission Disequilibrium Test in a Structured Population: Exact Formula," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-25, January.
    18. 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.
    19. Nick Patterson & Alkes L Price & David Reich, 2006. "Population Structure and Eigenanalysis," PLOS Genetics, Public Library of Science, vol. 2(12), pages 1-20, December.
    20. Ferguson John P. & Palejev Dean, 2014. "P-value calibration for multiple testing problems in genomics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(6), pages 659-673, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0019416. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.