Article
The Impact of Variable Degrees of Freedom and Scale Parameters in Bayesian Methods for Genomic Prediction in Chinese Simmental Beef Cattle.
PloS one - 1 Jan 2016
Zhu Bo, Zhu Miao, Jiang Jicai, Niu Hong, Wang Yanhui, Wu Yang, Xu Lingyang, Chen Yan, Zhang Lupei, Gao Xue, Gao Huijiang, Liu Jianfeng, Li Junya
Abstract excerpt
Three conventional Bayesian approaches (BayesA, BayesB and BayesCπ) have been demonstrated to be powerful in predicting genomic merit for complex traits in livestock. A priori, these Bayesian models assume that the non-zero SNP effects (marginally) follow a t-distribution depending on two fixed hyperparameters, degrees of freedom and scale parameters. In this study, we performed genomic prediction in Chinese...
Read the complete abstract on PubMedTopics
Share this publication in a Topic to start or enrich a Post.