Graduate School of Science and Technology, Niigata University, Nishi, Niigata, Japan.
Anim Sci J. 2009 Dec;80(6):617-23. doi: 10.1111/j.1740-0929.2009.00681.x.
Volumes of official data sets have been increasing rapidly in the genetic evaluation using the Japanese Black routine carcass field data. Therefore, an alternative approach with smaller memory requirement to the current one using the restricted maximum likelihood (REML) and the empirical best linear unbiased prediction (EBLUP) is desired. This study applied a Bayesian analysis using Gibbs sampling (GS) to a large data set of the routine carcass field data and practically verified its validity in the estimation of breeding values. A Bayesian analysis like REML-EBLUP was implemented, and the posterior means were calculated using every 10th sample from 90,000 of samples after 10,000 samples discarded. Moment and rank correlations between breeding values estimated by GS and REML-EBLUP were very close to one, and the linear regression coefficients and the intercepts of the GS on the REML-EBLUP estimates were substantially one and zero, respectively, showing a very good agreement between breeding value estimation by the current GS and the REML-EBLUP. The current GS required only one-sixth of the memory space with REML-EBLUP. It is confirmed that the current GS approach with relatively small memory requirement is valid as a genetic evaluation procedure using large routine carcass data.
利用日本黑猪常规胴体田间数据进行遗传评估时，官方数据集的数量迅速增加。因此，需要一种替代方法，该方法的内存要求小于当前使用限制最大似然（REML）和经验最佳线性无偏预测（EBLUP）的方法。本研究应用基于 Gibbs 抽样（GS）的贝叶斯分析对常规胴体田间数据的大型数据集进行了实际验证，并在估计育种值方面验证了其有效性。实施了类似于 REML-EBLUP 的贝叶斯分析，并使用丢弃 10,000 个样本后从 90,000 个样本中每 10 个样本计算后验均值。GS 估计的育种值与 REML-EBLUP 之间的矩相关系数和秩相关系数非常接近 1，GS 对 REML-EBLUP 估计值的线性回归系数和截距分别为 1 和 0，表明当前 GS 对育种值的估计和 REML-EBLUP 之间具有非常好的一致性。GS 当前所需的内存空间仅为 REML-EBLUP 的六分之一。证实了具有相对较小内存要求的当前 GS 方法可作为使用大型常规胴体数据进行遗传评估的有效方法。
