Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance.
Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance.
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DOI：
10.1186/1297-9686-42-9
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发表时间：
2010-03-22
期刊：
影响因子：
--
通讯作者：
Bovenhuis H
中科院分区：
文献类型：
--
作者：
Coster A;Bastiaansen JW;Calus MP;van Arendonk JA;Bovenhuis H
本模拟研究的目的是比较QTL数目和QTL方差分布对利用全基因组标记(MEBV)估计育种值的准确性的影响。用三种不同的方法计算MEBV：贝叶斯方法(BM)、最小角度回归(LARS)和偏最小二乘回归(PLSR)。随着模拟QTL数目的增加，用BM和LARS计算的MEBV的精度降低。当QTL具有不同的方差值时，比当所有QTL具有相同的方差值时，精度下降得更多。用PLSR计算MEBV的准确性既不受QTL数目的影响，也不受QTL方差分布的影响。进一步的模拟和分析表明，这些结论不受训练群体中的个体数量、标记数量和性状遗传力的影响。研究结果表明，QTL个数和QTL方差分布对MEBV精度的影响取决于MEBV的计算方法。
The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV.
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影响因子：
1.5
作者：
Goddard, Mike
通讯作者：
Goddard, Mike
影响因子：
3.3
作者：
Calus, M P L;Meuwissen, T H E;Veerkamp, R F
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影响因子：
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作者：
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DOI：
10.1016/0169-7439(93)85002-x
发表时间：
1993-03-01
影响因子：
3.9
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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