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Association tests through combining p-values for case control genome-wide association studies

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  • Chen, Zhongxue

Abstract

To detect single nucleotide polymorphisms (SNPs) that are associated with a common disease in a case control genome-wide association study (GWAS), powerful yet robust tests are desirable. Current available robust approaches in this area are mainly based on the optimal trend tests for some specific genetic models, such as recessive, additive, multiplicative, and dominant models. In this paper, we propose a class of robust association tests through combining p-values obtained by partitioning the 2 by 3 contingency table of the SNP data. Through simulation study and application to real data, we show that the proposed tests are powerful and robust. They provide alternative association tests for GWAS.

Suggested Citation

  • Chen, Zhongxue, 2013. "Association tests through combining p-values for case control genome-wide association studies," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1854-1862.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:8:p:1854-1862
    DOI: 10.1016/j.spl.2013.04.021
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    References listed on IDEAS

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    1. 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).
    2. Jungnam Joo & Minjung Kwak & Gang Zheng, 2010. "Improving Power for Testing Genetic Association in Case–Control Studies by Reducing the Alternative Space," Biometrics, The International Biometric Society, vol. 66(1), pages 266-276, March.
    3. 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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    Cited by:

    1. Chen, Zhongxue & Huang, Hanwen & Ng, Hon Keung Tony, 2014. "An improved robust association test for GWAS with multiple diseases," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 153-161.
    2. Chen, Zhongxue & Nadarajah, Saralees, 2014. "On the optimally weighted z-test for combining probabilities from independent studies," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 387-394.
    3. Chen Zhongxue & Han Shizhong & Wang Kai, 2017. "Genetic association test based on principal component analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(3), pages 189-198, August.

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