中文摘要：

引起价值的 genomic 的评价在 genomic 选择是重要的。贝叶斯并且 BLUP 方法是采用的主要技术。在这研究，我们在模仿的数据和中国荷兰的一种乳牛牛的真实数据进行了 BayesA， BayesB， BayesC 和 GBLUP 方法的比较研究。结果证明在模仿的数据，所有方法的精确性都同样随参考人口尺寸的增加被提高，但是他们做了不同回答到标记数字或 QTL 数字的变化。在中国荷兰的一种乳牛牛的真实数据， BayesA 几乎为所有六个特点产生了最高的精确性，并且 GBLUP 为，产量，胖收益和蛋白质为胖百分比，蛋白质百分比和体的房间分数的特点产出的牛奶的特点象 BayesA 一样表现了，三个贝叶斯的方法显示出上级到 GBLUP 。包括地上面分析结果，三个贝叶斯的方法的精确性是，这能被推测不仅由 QTL 数字或标记数字的绝对值影响了，而且可以被 QTL 数字的比率也影响到标记数字。并且有至少一个种贝叶斯的方法，比 GBLUP 更好表现，当 QTL 数字的比率对标记数字是很小或包含的大效果的 QTL 时。

英文摘要：

Estimation of genomic breeding values is important in genomic selection. Bayesian and BLUP methods are the main techniques employed. In this study,we conducted a comparative study of Bayes A, Bayes B,Bayes Cp and GBLUP methods in simulated data and real data of Chinese Holstein cattle. Results showed that, in simulated data, the accuracies of all methods were all similarly elevated with the increase of reference population size, but they made different responses to the changes of marker number or QTL number. In real data of Chinese Holstein cattle, Bayes A generated the highest accuracy almost for all six traits, and GBLUP performed as well as Bayes A for the traits of milk yield, fat yield and protein yield, while for the trait of fat percentage, protein percentage and somatic cell score, three Bayesian methods showed superior to GBLUP. Comprehensively analyzing above results, it can be speculated that accuracies of the three Bayesian methods are not only influenced by the absolute value of QTL number or marker number, but may also be influenced by the ratio of QTL number to marker number. And there is at least one kind of Bayesian methods performing better than GBLUP, when the ratio of QTL number versus marker number is very small or involving large-effect QTL.