A model selection approach for the identification of quantitative trait loci in experimental crosses
A model selection approach for the identification of quantitative trait loci in experimental crosses
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DOI：
10.1111/1467-9868.00354
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发表时间：
2002-01-01
影响因子：
5.8
通讯作者：
Speed, TP
中科院分区：
文献类型：
--
作者：
Broman, KW;Speed, TP
我们考虑的问题，确定的遗传位点（称为数量性状位点（QTL））的数量性状的变异，与实验杂交的数据。已经描述了大量不同的统计方法来解决这个问题;大多数使用多个假设检验，许多考虑模型只允许一个QTL。我们认为，最好把这个问题看作是一个模式选择问题。我们讨论了利用模型选择的思想来确定QTL在实验杂交。我们专注于一个回交试验，严格加性QTL，并集中在确定QTL，考虑估计他们的影响和精确的位置，次要的。我们提出了一个模拟研究的结果，比较更突出的方法的性能。
We consider the problem of identifying the genetic loci (called quantitative trait loci (QTLs)) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel that the problem is best viewed as one of model selection. We discuss the use of model selection ideas to identify QTLs in experimental crosses. We focus on a back-cross experiment, with strictly additive QTLs, and concentrate on identifying QTLs, considering the estimation of their effects and precise locations of secondary importance. We present the results of a simulation study to compare the performances of the more prominent methods.