The use of weighted multiple linear regression to estimate QTL-by-QTL epistatic effects.
The use of weighted multiple linear regression to estimate QTL-by-QTL epistatic effects.
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使用加权多个线性回归来估计by-qtl上位效应。
DOI：
10.1590/s1415-47572012005000071
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发表时间：
2012-12
影响因子：
2.1
通讯作者：
Bocianowski J
中科院分区：
文献类型：
--
作者：
Bocianowski J
了解基因效应的性质和大小，以及它们对计量性状控制的贡献，对于制定有效的育种计划以改善植物遗传是重要的。有关遗传参数的信息，如加性对加性的上位效应，在传统育种中是有用的。本文描述了用加权多元线性回归估计与加性-加性-加性上位相互作用有关的参数所得到的结果。使用了三种权重变量：(1)基于估计方差的标准权重；(2)最小值、最大值和其他线的不同权重；(3)极端值和其他线的不同权重。这里描述的方法结合了两种估计方法，一种基于表型观察，另一种使用分子标记数据。采用蒙特卡罗模拟方法进行了比较。结果表明，对标记数据应用加权回归得到的估计与表型方法得到的估计相似。
Knowledge of the nature and magnitude of gene effects, as well as their contribution to the control of metric traits, is important in formulating efficient breeding programs for the improvement of plant genetics. Information concerning a genetic parameter such as the additive-by-additive epistatic effect can be useful in traditional breeding. This report describes the results obtained by applying weighted multiple linear regression to estimate the parameter connected with an additive-by-additive epistatic interaction. Three weight variants were used: (1) standard weights based on estimated variances, (2) different weights for minimal, maximal and other lines, and (3) different weights for extreme and other lines. The approach described here combines two methods of estimation, one based on phenotypic observations and the other using molecular marker data. The comparison was done using Monte Carlo simulations. The results show that the application of weighted regression to the marker data yielded estimates similar to those obtained by phenotypic methods.
影响因子：
2.1
作者：
Lau CH;Muniandy S
通讯作者：
Muniandy S