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在非匹配病例对照数据分析中检验哈迪-温伯格平衡的价值:一则警示

The merits of testing Hardy-Weinberg equilibrium in the analysis of unmatched case-control data: a cautionary note.

作者信息

Zou Guang Yong, Donner Allan

机构信息

Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.

出版信息

Ann Hum Genet. 2006 Nov;70(Pt 6):923-33. doi: 10.1111/j.1469-1809.2006.00267.x.

Abstract

Testing for departures from the assumption of Hardy-Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case-control studies. Some authors suggest using a two-stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi-square procedure or the Cochran-Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi-square test statistic, a procedure which in the present context is identical to the trend test. Examples from previous reports are used to illustrate the methodology.

摘要

作为基因病例对照研究分析的初步步骤,广泛推荐对哈迪-温伯格平衡(HWE)假设的偏离情况进行检验。一些作者建议采用两阶段程序,其中最终使用Pearson卡方程序或Cochran-Armitage趋势检验来评估基因/疾病关联。其他作者则更进一步,鼓励研究人员舍弃违反HWE的数据,本质上是将该检验用作识别基因分型错误的工具。在本文中,我们表明:1)不应将HWE检验用作识别基因分型错误的工具;2)在检验等位基因与疾病之间的关联之前,检验HWE假设既无必要,甚至可能有害。相反,应该使用调整后的卡方检验统计量固有地考虑偏离HWE的情况,在当前背景下,该程序与趋势检验相同。使用先前报告中的示例来说明该方法。

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