IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0074310.html
   My bibliography  Save this article

Detecting Rare Variants in Case-Parents Association Studies

Author

Listed:
  • Kuang-Fu Cheng
  • Jin-Hua Chen

Abstract

Despite the success of genome-wide association studies (GWASs) in detecting common variants (minor allele frequency ≥0.05) many suggested that rare variants also contribute to the genetic architecture of diseases. Recently, researchers demonstrated that rare variants can show a strong stratification which may not be corrected by using existing methods. In this paper, we focus on a case-parents study and consider methods for testing group-wise association between multiple rare (and common) variants in a gene region and a disease. All tests depend on the numbers of transmitted mutant alleles from parents to their diseased children across variants and hence they are robust to the effect of population stratification. We use extensive simulation studies to compare the performance of four competing tests: the largest single-variant transmission disequilibrium test (TDT), multivariable test, combined TDT, and a likelihood ratio test based on a random-effects model. We find that the likelihood ratio test is most powerful in a wide range of settings and there is no negative impact to its power performance when common variants are also included in the analysis. If deleterious and protective variants are simultaneously analyzed, the likelihood ratio test was generally insensitive to the effect directionality, unless the effects are extremely inconsistent in one direction.

Suggested Citation

  • Kuang-Fu Cheng & Jin-Hua Chen, 2013. "Detecting Rare Variants in Case-Parents Association Studies," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-9, September.
    • Handle: RePEc:plo:pone00:0074310
    DOI: 10.1371/journal.pone.0074310
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0074310
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0074310&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0074310?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. Brendan Maher, 2008. "Personal genomes: The case of the missing heritability," Nature, Nature, vol. 456(7218), pages 18-21, November.
    Full references (including those not matched with items on IDEAS)

    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. Chuong B Do & David A Hinds & Uta Francke & Nicholas Eriksson, 2012. "Comparison of Family History and SNPs for Predicting Risk of Complex Disease," PLOS Genetics, Public Library of Science, vol. 8(10), pages 1-16, October.
    2. Iuliana Ionita-Laza & Joseph D Buxbaum & Nan M Laird & Christoph Lange, 2011. "A New Testing Strategy to Identify Rare Variants with Either Risk or Protective Effect on Disease," PLOS Genetics, Public Library of Science, vol. 7(2), pages 1-6, February.
    3. Aida Bianco & Eusebio Chiefari & Carmelo G A Nobile & Daniela Foti & Maria Pavia & Antonio Brunetti, 2015. "The Association between HMGA1 rs146052672 Variant and Type 2 Diabetes: A Transethnic Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-15, August.
    4. Yumei Yang & Qishan Wang & Qiang Chen & Rongrong Liao & Xiangzhe Zhang & Hongjie Yang & Youmin Zheng & Zhiwu Zhang & Yuchun Pan, 2014. "A New Genotype Imputation Method with Tolerance to High Missing Rate and Rare Variants," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-7, June.
    5. Chung-Feng Kao & Jia-Rou Liu & Hung Hung & Po-Hsiu Kuo, 2015. "A Robust GWSS Method to Simultaneously Detect Rare and Common Variants for Complex Disease," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-14, April.
    6. Dominic Russ & John A Williams & Victor Roth Cardoso & Laura Bravo-Merodio & Samantha C Pendleton & Furqan Aziz & Animesh Acharjee & Georgios V Gkoutos, 2022. "Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-19, February.
    7. von Stumm, Sophie & Kandaswamy, Radhika & Maxwell, Jessye, 2023. "Gene-environment interplay in early life cognitive development," Intelligence, Elsevier, vol. 98(C).
    8. Charles-Elie Rabier & Philippe Barre & Torben Asp & Gilles Charmet & Brigitte Mangin, 2016. "On the Accuracy of Genomic Selection," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-23, June.
    9. Janet Currie, 2011. "Ungleichheiten bei der Geburt: Einige Ursachen und Folgen," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 12(s1), pages 42-65, May.
    10. Karen Kapur & Toby Johnson & Noam D Beckmann & Joban Sehmi & Toshiko Tanaka & Zoltán Kutalik & Unnur Styrkarsdottir & Weihua Zhang & Diana Marek & Daniel F Gudbjartsson & Yuri Milaneschi & Hilma Holm , 2010. "Genome-Wide Meta-Analysis for Serum Calcium Identifies Significantly Associated SNPs near the Calcium-Sensing Receptor (CASR) Gene," PLOS Genetics, Public Library of Science, vol. 6(7), pages 1-12, July.
    11. Kettlewell, Nathan & Tymula, Agnieszka & Yoo, Hong Il, 2023. "The Heritability of Economic Preferences," IZA Discussion Papers 16633, Institute of Labor Economics (IZA).
    12. Gang Fang & Majda Haznadar & Wen Wang & Haoyu Yu & Michael Steinbach & Timothy R Church & William S Oetting & Brian Van Ness & Vipin Kumar, 2012. "High-Order SNP Combinations Associated with Complex Diseases: Efficient Discovery, Statistical Power and Functional Interactions," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-15, April.
    13. Kozlitina Julia & Schucany William R., 2015. "A robust distribution-free test for genetic association studies of quantitative traits," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(5), pages 443-464, November.
    14. Le Rouzic, Arnaud & Skaug, Hans J. & Hansen, Thomas F., 2010. "Estimating genetic architectures from artificial-selection responses: A random-effect framework," Theoretical Population Biology, Elsevier, vol. 77(2), pages 119-130.
    15. Janet Currie, 2011. "Inequality at Birth: Some Causes and Consequences," American Economic Review, American Economic Association, vol. 101(3), pages 1-22, May.
    16. Shashaank Vattikuti & Juen Guo & Carson C Chow, 2012. "Heritability and Genetic Correlations Explained by Common SNPs for Metabolic Syndrome Traits," PLOS Genetics, Public Library of Science, vol. 8(3), pages 1-8, March.
    17. Xinge Jessie Jeng & Zhongyin John Daye & Wenbin Lu & Jung-Ying Tzeng, 2016. "Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-23, June.
    18. Pan, Qing & Zhao, Yunpeng, 2016. "Integrative weighted group lasso and generalized local quadratic approximation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 66-78.
    19. Qiuyi Zhang & Yang Zhao & Ruyang Zhang & Yongyue Wei & Honggang Yi & Fang Shao & Feng Chen, 2016. "A Comparative Study of Five Association Tests Based on CpG Set for Epigenome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-13, June.
    20. Gabriel E Hoffman & Benjamin A Logsdon & Jason G Mezey, 2013. "PUMA: A Unified Framework for Penalized Multiple Regression Analysis of GWAS Data," PLOS Computational Biology, Public Library of Science, vol. 9(6), pages 1-19, June.

    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:pone00:0074310. 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.