基于生物模型的双列分析混合模型方法。

Mixed model approaches for diallel analysis based on a bio-model.

作者信息

Zhu J, Weir B S

机构信息

Department of Agronomy, Zhejiang Agricultural University, Hangzhou, China.

出版信息

Genet Res. 1996 Dec;68(3):233-40. doi: 10.1017/s0016672300034200.

DOI:10.1017/s0016672300034200

PMID:9062080

Abstract

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

摘要

本文提出了一种MINQUE(1)方法，即对所有先验值均为1的最小范数二次无偏估计（MINQUE）方法，用于估计双列杂交生物模型中的方差和协方差分量。比较了MINQUE(1)、约束最大似然法（REML）和具有先验值参数的MINQUE θ在估计无偏性和效率方面的差异。在对遗传方差和协方差分量进行无偏估计时，MINQUE(1)的效率几乎与MINQUE θ相同。该生物模型在估计母本和父本效应以及核效应的方差和协方差分量方面是有效且稳健的。本文还提出了一种调整无偏预测（AUP）程序，用于预测生物模型中的随机遗传效应。建议采用刀切法来估计估计方差和协方差分量以及预测遗传效应的抽样方差。文中给出了估计方差和协方差分量以及预测遗传价值的实例。