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文章基本信息

  • 标题:A robust test for quantitative trait analysis with model uncertainty in genetic association studies
  • 作者:Qizhai Li ; Wenjun Xiong ; Jinbo Chen
  • 期刊名称:Statistics and Its Interface
  • 印刷版ISSN:1938-7989
  • 电子版ISSN:1938-7997
  • 出版年度:2014
  • 卷号:7
  • 期号:1
  • 页码:61-68
  • DOI:10.4310/SII.2014.v7.n1.a7
  • 出版社:International Press
  • 摘要:Statistical tests that assume an additive model are commonly employed in genetic association studies. However, the true models for genetic variants are rarely known. A mis-specified genetic model may lead to loss of power in identifying the potential markers associated with a disease. In this paper, we develop a robust test based on modified $F$-test statistics for quantitative trait genetic association studies and a simple method to compute its statistical significance and power. We also study sample size calculations for designing such an association study. Numerical results, including simulation studies and a real data example, show that the proposed robust test has satisfactory performance when the model is unknown and is more robust than some existing procedures when the model is mis-specified.
  • 关键词:$F$-test; robust; quantitative trait; genome-wide association studies
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