Demenais F, Lathrop M, Lalouel J M
Am J Hum Genet. 1986 Feb;38(2):228-34.
The resolution between skewness in the distribution of a quantitative trait and segregation of a major gene is a difficult issue in family studies. Quantitative data were simulated on six-member nuclear families in order to study the behavior of the unified model under these circumstances. Replicates of 100 nuclear families were generated assuming a multifactorial model with skewness. In the range where a major gene was falsely detected in 80%-100% of the simulations analyzed under the transmission probability or mixed models, use of the unified model reduces the frequency of false inference to between 10% and 40%. This protection against a false conclusion requires estimation of the three transmission probabilities and testing hypotheses of Mendelian transmission and equal transmission probabilities. Alternatively, it was shown that use of a transformation to remove skewness induced by a major gene leads to a decrease of power of approximately 55%. These results suggest that the unified model may obviate the need to compare analyses performed on transformed and untransformed data, particularly when skewness is low (less than 0.2) or high (greater than 0.4). For intermediate skewness (0.2-0.4), estimating segregation parameters under the mixed model simultaneously with a transformation to remove residual skewness can be considered as an alternative method.
在家庭研究中，解决数量性状分布的偏态与主基因分离之间的问题是一个难题。为了研究统一模型在这些情况下的行为，对六口之家的核心家庭进行了数量数据模拟。假设存在具有偏态的多因素模型，生成了100个核心家庭的重复样本。在根据传递概率或混合模型分析的模拟中，在80%-100%的模拟中错误检测到主基因的范围内，使用统一模型可将错误推断的频率降低到10%至40%之间。避免得出错误结论需要估计三个传递概率，并检验孟德尔传递和相等传递概率的假设。另外，研究表明，使用变换来消除主基因引起的偏态会导致检验效能下降约55%。这些结果表明，统一模型可能无需比较对变换后和未变换数据进行的分析，特别是当偏态较低（小于0.2）或较高（大于0.4）时。对于中等偏态（0.2-0.4），可以考虑在混合模型下估计分离参数，同时进行变换以消除残留偏态，作为一种替代方法。
