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An improved robust association test for GWAS with multiple diseases

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  • Chen, Zhongxue
  • Huang, Hanwen
  • Ng, Hon Keung Tony

Abstract

In a previous study, we proposed a new design and analysis strategy for Genome-wide Association Studies (GWAS) with multiple diseases but no controls. We have proposed to use an overall chi-square test to test for the association between an SNP with any one of the diseases. The overall chi-square test is not sensitive to the underlying model assumption; however, it does not use the information about the trend among the relative risks of the three genotypes. In this study, we propose a new overall test based on the chi-square partition method. The overall p-value of the proposed approach can be estimated by combining independent p-values from the more powerful one-sided tests which incorporate the trend among the relative risks. Simulation study and real data application show that the proposed test is more powerful and robust.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:stapro:v:91:y:2014:i:c:p:153-161
    DOI: 10.1016/j.spl.2014.04.015
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    References listed on IDEAS

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    1. LOUISE M. RYAN & Boris Freidlin & Marvin J. Podgor & Joseph L. Gastwirth, 1999. "Efficiency Robust Tests for Survival or Ordered Categorical Data," Biometrics, The International Biometric Society, vol. 55(3), pages 883-886, September.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
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