Hoeschele I, VanRaden P M
Department of Dairy Science, Virginia Polytechnic Institute and State University, Blacksburg 24061-6999.
J Dairy Sci. 1991 Feb;74(2):557-69. doi: 10.3168/jds.S0022-0302(91)78203-9.
For estimation of dominance effects and dominance variance, the inverse of a dominance relationship matrix is required. Dominance effects can be partitioned into sire x dam or sire x maternal grandsire subclass effects that are inherited and residuals within subclass that are not inherited. The subclass effects have immediate use in predicting performance of offspring from prospective matings. A rapid method for directly computing the inverse relationship matrix of subclass effects is presented. The procedure is similar to Henderson's simple method of computing an inverse additive genetic relationship matrix. The inverse relationship matrix among subclass effects consists of a contribution from each subclass of coefficients of a matrix of maximum size 9 x 9. The algorithm can be modified to compute the inverse of the relationship matrix among sire x dam or sire x maternal grandsire subclasses and among individual dominance effects. Computing cost increases approximately linearly with dimensions of inverses. Dimensions could be several times the number of subclasses in the data because subclasses without records but providing relationship ties must be added. Computation of the inverse relationship matrix among 136,827 sire x maternal grandsire subclasses in a population of 765,868 animals required 163 central processing unit seconds on an IBM 3090 and less than 4 Mbytes of memory.
为了估计显性效应和显性方差,需要一个显性关系矩阵的逆矩阵。显性效应可以被划分为父本×母本或父本×母系祖父亚类效应(这些效应是可遗传的)以及亚类内不可遗传的残差。亚类效应可直接用于预测预期交配后代的表现。本文提出了一种直接计算亚类效应逆关系矩阵的快速方法。该过程类似于亨德森计算逆加性遗传关系矩阵的简单方法。亚类效应之间的逆关系矩阵由一个最大尺寸为9×9的矩阵中每个亚类的系数贡献组成。该算法可以修改为计算父本×母本或父本×母系祖父亚类之间以及个体显性效应之间的关系矩阵的逆矩阵。计算成本随逆矩阵的维度近似线性增加。维度可能是数据中亚类数量的几倍,因为必须添加没有记录但提供关系纽带的亚类。在一个拥有765,868只动物的群体中,计算136,827个父本×母系祖父亚类之间的逆关系矩阵,在IBM 3090上需要163个中央处理器秒,内存使用不到4兆字节。