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Genetic association test based on principal component analysis

Author

Listed:
  • Chen Zhongxue

    (Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E. 7th Street, Bloomington, IN 47405, USA)

  • Han Shizhong

    (Department of Psychiatry, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA)

  • Wang Kai

    (Department of Biostatistics, N322 CPHB College of Public Health, University of Iowa, 145 N. Riverside Drive, Iowa City, IA 52242, USA)

Abstract

Many gene- and pathway-based association tests have been proposed in the literature. Among them, the SKAT is widely used, especially for rare variants association studies. In this paper, we investigate the connection between SKAT and a principal component analysis. This investigation leads to a procedure that encompasses SKAT as a special case. Through simulation studies and real data applications, we compare the proposed method with some existing tests.

Suggested Citation

  • 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.
  • Handle: RePEc:bpj:sagmbi:v:16:y:2017:i:3:p:189-198:n:2
    DOI: 10.1515/sagmb-2016-0061
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    References listed on IDEAS

    as
    1. 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.
    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.
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