Association mapping in a simulated barley population
Association mapping in a simulated barley population
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DOI：
10.1007/s10681-011-0505-z
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发表时间：
2012-02-01
期刊：
影响因子：
1.9
通讯作者：
Hackett, Christine A.
中科院分区：
文献类型：
--
作者：
MacKenzie, Katrin;Hackett, Christine A.
群体内部的子结构往往使关联映射群体的分析变得复杂。如果这种情况没有得到解释，通常会导致许多假阳性的标记-性状关联。在这项研究中，我们模拟了一个大的大麦群体，模拟了近交和选择，并比较了五种分析标记-性状关联的模型。其中一个不包括群体子结构，一个包括地理来源和大麦类型的信息，以代表群体内部的结构，三个使用不同的方法来估计基于标记的亲属关系。与其他模型相比，亲属关系方法大大减少了假阳性的数量，但这些方法都没有明显的优势。一种解决方案是拟合多个模型，并将那些对所有模型都重要的标记视为候选关联。在考虑的最低遗传率水平（25%）下，没有一种方法在检测真正的关联方面非常成功，这表明在关联映射研究中考虑权力是重要的，以避免遗漏一些真正的关联和高估其他关联。
The analysis of association mapping populations is frequently complicated by substructure within the population. If this is unaccounted for, it generally results in many false positive marker-trait associations. In this study, we simulate a large barley population, modelling inbreeding and selection, and compare five models for analysing marker-trait associations. One of these includes no population substructure, one includes information about geographical origin and type of barley to represent structure within the population and three use different approaches that have been proposed for estimating marker-based kinship. Kinship methods reduced the number of false positives substantially compared to the other models but none of these approaches had a clear advantage over the others. One solution is to fit more than one model and to consider as candidate associations those markers that are significant by all models. None of the approaches were very successful at detecting true associations at the lowest level of heritability considered (25%), suggesting it is important to consider power in association mapping studies to avoid missing some true associations and overestimating others.