Diao G, Lin D Y
Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599-7420, USA.
Am J Hum Genet. 2005 Jul;77(1):97-111. doi: 10.1086/431683. Epub 2005 May 25.
The variance-components model is the method of choice for mapping quantitative trait loci in general human pedigrees. This model assumes normally distributed trait values and includes a major gene effect, random polygenic and environmental effects, and covariate effects. Violation of the normality assumption has detrimental effects on the type I error and power. One possible way of achieving normality is to transform trait values. The true transformation is unknown in practice, and different transformations may yield conflicting results. In addition, the commonly used transformations are ineffective in dealing with outlying trait values. We propose a novel extension of the variance-components model that allows the true transformation function to be completely unspecified. We present efficient likelihood-based procedures to estimate variance components and to test for genetic linkage. Simulation studies demonstrated that the new method is as powerful as the existing variance-components methods when the normality assumption holds; when the normality assumption fails, the new method still provides accurate control of type I error and is substantially more powerful than the existing methods. We performed a genomewide scan of monoamine oxidase B for the Collaborative Study on the Genetics of Alcoholism. In that study, the results that are based on the existing variance-components method changed dramatically when three outlying trait values were excluded from the analysis, whereas our method yielded essentially the same answers with or without those three outliers. The computer program that implements the new method is freely available.
方差成分模型是在一般人类家系中定位数量性状基因座的首选方法。该模型假设性状值呈正态分布，并包括一个主基因效应、随机多基因效应和环境效应以及协变量效应。违反正态性假设会对I型错误率和检验效能产生不利影响。实现正态性的一种可能方法是对性状值进行变换。在实际中真实的变换是未知的，并且不同的变换可能会产生相互矛盾的结果。此外，常用的变换在处理异常性状值时效果不佳。我们提出了方差成分模型的一种新颖扩展，它允许完全不指定真实的变换函数。我们给出了基于似然的有效方法来估计方差成分并检验遗传连锁。模拟研究表明，当正态性假设成立时，新方法与现有的方差成分方法具有相同的检验效能；当正态性假设不成立时，新方法仍然能够准确控制I型错误率，并且检验效能比现有方法高得多。我们对酒精中毒遗传学合作研究中的单胺氧化酶B进行了全基因组扫描。在该研究中，当从分析中排除三个异常性状值时，基于现有方差成分方法的结果发生了巨大变化，而我们的方法无论是否包含这三个异常值都得出了基本相同的答案。实现新方法的计算机程序可免费获取。
