Varona L, Gómez-Raya L, Rauw W M, Clop A, Ovilo C, Noguera J L
Area de Producció Animal, Centre UdL-IRTA, Lleida, 25198, Spain.
Genetics. 2004 Feb;166(2):1025-35. doi: 10.1534/genetics.166.2.1025.
A simple procedure to calculate the Bayes factor between linked and pleiotropic QTL models is presented. The Bayes factor is calculated from the marginal prior and posterior densities of the locations of the QTL under a linkage and a pleiotropy model. The procedure is computed with a Gibbs sampler, and it can be easily applied to any model including the location of the QTL as a variable. The procedure was compared with a multivariate least-squares method. The proposed procedure showed better results in terms of power of detection of linkage when low information is available. As information increases, the performance of both procedures becomes similar. An example using data provided by an Iberian by Landrace pig intercross is presented. The results showed that three different QTL segregate in SSC6: a pleiotropic QTL affects myristic, palmitic, and eicosadienoic fatty acids; another pleiotropic QTL affects palmitoleic, stearic, and vaccenic fatty acids; and a third QTL affects the percentage of linoleic acid. In the example, the Bayes factor approach was more powerful than the multivariate least-squares approach.
本文提出了一种计算连锁和多效性QTL模型之间贝叶斯因子的简单方法。贝叶斯因子是根据连锁模型和多效性模型下QTL位置的边际先验密度和后验密度计算得出的。该方法通过吉布斯采样器进行计算，并且可以很容易地应用于任何将QTL位置作为变量的模型。将该方法与多元最小二乘法进行了比较。当可用信息较少时，所提出的方法在连锁检测能力方面表现出更好的结果。随着信息的增加，两种方法的性能变得相似。给出了一个使用伊比利亚猪与长白猪杂交后代数据的例子。结果表明，在猪的6号染色体上有三个不同的QTL分离：一个多效性QTL影响肉豆蔻酸、棕榈酸和二十碳二烯酸；另一个多效性QTL影响棕榈油酸、硬脂酸和反式vaccenic酸；第三个QTL影响亚油酸的百分比。在该例子中，贝叶斯因子方法比多元最小二乘法更有效。
