Fulker D W, Cherny S S
Institute for Behavioral Genetics, University of Colorado, Boulder 80309-0447, USA.
Behav Genet. 1996 Sep;26(5):527-32. doi: 10.1007/BF02359758.
Kruglyak and Lander (1995) recently published a multipoint sib-pair procedure based on the expected distribution of zero, one and two marker alleles shared identical by descent (ibd) and the method of maximum-likelihood (ML). Their approach uses phenotypic sib-pair differences, which ignores the bivariate structure of sib-pair data. Their simulations suggested that their method was more powerful than the regression method of Haseman and Elston (1972). We show through computation and simulation that their approach can be made more powerful still if the bivariate nature of sib-pair data is acknowledged. In addition, methods based on the average number of shared alleles that also employ bivariate ML procedures (Nance and Neale, 1989; Xu and Atchley, 1995) are more powerful than the approach they recommend and very similar to true ML using the distribution of ibd. The simple ML approach using the average number of shared alleles that we recommend seems to offer both optimal power and flexibility.
克鲁格利亚克和兰德(1995年)最近发表了一种基于零个、一个和两个通过血缘相同的标记等位基因(ibd)的预期分布以及最大似然法(ML)的多点同胞对程序。他们的方法使用表型同胞对差异,忽略了同胞对数据的双变量结构。他们的模拟表明,他们的方法比哈斯曼和埃尔斯顿(1972年)的回归方法更有效。我们通过计算和模拟表明,如果承认同胞对数据的双变量性质,他们的方法可以变得更有效。此外,基于共享等位基因平均数且也采用双变量ML程序的方法(南斯和尼尔,1989年;徐和阿奇利,1995年)比他们推荐的方法更有效,并且与使用ibd分布的真正ML非常相似。我们推荐的使用共享等位基因平均数的简单ML方法似乎提供了最佳的功效和灵活性。