Arakawa Aisaku, Taniguchi Masaaki, Hayashi Takeshi, Mikawa Satoshi
Animal Genome Research Unit, National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan.
Agroinformatics Division, National Agriculture and Food Research Organization, Agricultural Research Center, Tsukuba, Ibaraki, Japan.
Anim Sci J. 2016 Jul;87(7):863-72. doi: 10.1111/asj.12514. Epub 2016 Feb 15.
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
我们通过使用变分推理方法（即所谓的变分贝叶斯方法）开发了一种贝叶斯分析方法，以确定方差分量的后验分布。在从模拟数据和公开可用的真实猪数据估计遗传方差分量和残差方差分量时，对这种变分贝叶斯方法与使用吉布斯采样的另一种贝叶斯方法进行了比较。在模拟数据集中，我们观察到，在低遗传力和低群体规模的情况下，变分贝叶斯方法对遗传方差的估计存在强烈的高估偏差，而在两种方法中，群体规模较大时检测到的偏差较小。在真实猪数据中未发现变分贝叶斯方法和吉布斯采样在方差分量估计上的差异。然而，用变分贝叶斯方法获得的方差分量的后验分布的尾部比用吉布斯采样获得的要短。因此，变分贝叶斯方法的遗传方差和残差方差的后验标准差低于使用吉布斯采样的方法。变分贝叶斯方法所需的计算时间比使用吉布斯采样的方法短得多。
