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Combining dependent F-tests for robust association of quantitative traits under genetic model uncertainty

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  • Qu Long

    (Department of Mathematics & Statistics, Wright State University, Dayton, OH 45435, USA)

Abstract

In association mapping of quantitative traits, the F-test based on an assumed genetic model is a basic statistical tool for testing association of each candidate locus with the trait of interest. However, the true underlying genetic model is often unknown, and using an incorrect model may cause serious loss of power. For case-control studies, it is known that the combination of several tests that are optimal for different models is robust to model misspecification. In this paper, we extend the test combination approach to quantitative trait association. We first derive the exact correlations among transformed test statistics and discuss interesting special cases. We then propose and evaluate a multivariate normality based approximation to the joint distribution of test statistics, such that the marginal distributions and pairwise correlations among test statistics are accounted for. Through simulations, we show that the sizes of the resulting approximate combined tests are accurate for practical purposes under a variety of situations. We find that the combination of the tests from the additive model and the genotypic model performs well, because it demonstrates both robustness to incorrect models and satisfactory power. A mouse lipoprotein data set is used to demonstrate the method.

Suggested Citation

  • Qu Long, 2014. "Combining dependent F-tests for robust association of quantitative traits under genetic model uncertainty," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(2), pages 123-139, April.
    • Handle: RePEc:bpj:sagmbi:v:13:y:2014:i:2:p:123-139:n:1
    DOI: 10.1515/sagmb-2013-0001
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    References listed on IDEAS

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    1. Buhm Han & Hyun Min Kang & Eleazar Eskin, 2009. "Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers," PLOS Genetics, Public Library of Science, vol. 5(4), pages 1-13, April.
    2. Zang, Yong & Fung, Wing Kam & Zheng, Gang, 2010. "Simple Algorithms to Calculate Asymptotic Null Distributions of Robust Tests in Case-Control Genetic Association Studies in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i08).
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    6. Jan R. Magnus, 1986. "The Exact Moments of a Ratio of Quadratic Forms in Normal Variables," Annals of Economics and Statistics, GENES, issue 4, pages 95-109.
    7. Minjung Kwak & Jungnam Joo & Gang Zheng, 2009. "A Robust Test for Two-Stage Design in Genome-Wide Association Studies," Biometrics, The International Biometric Society, vol. 65(4), pages 1288-1295, December.
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