Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data
Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data
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DOI：
10.1086/302891
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发表时间：
2000-05-01
影响因子：
9.8
通讯作者：
Hewitt, JK
中科院分区：
文献类型：
--
作者：
Sham, PC;Cherny, SS;Hewitt, JK
数量性状基因座（QTL）定位研究的优化设计需要精确了解QTL连锁与QTL关联分析在不同条件下的作用。在这篇文章中，我们调查的权力QTL的连锁和关联分析的简单随机同胞样本下，由Fulker等人提出的方差分量模型。在此方差分量模型的扩展的简要说明后，我们表明，连锁和关联分析的权力是至关重要的依赖于归因于QTL的表型方差的比例。这两种检验的主要区别在于，关联力与QTL遗传力直接相关，而连锁力与QTL遗传力的平方更密切相关。我们还描述了不完全连锁和不完全标记信息是如何削弱连锁的力量，以及不完全连锁不平衡是如何削弱关联的力量。
Optimal design of quantitative-trait loci (QTL) mapping studies requires a precise understanding of the power of QTL linkage versus QTL association analysis, under a range of different conditions. In this article, we investigate the power of QTL linkage and association analyses for simple random sibship samples, under the variance-components model proposed by Fulker et al. After a brief description of an extension of this variance-components model, we show that the powers of both linkage and association analyses are crucially dependent on the proportion of phenotypic variance attributable to the QTL. The main difference between the two tests is that, whereas the power of association is directly related to the QTL heritability, the power of linkage is related more closely to the square of the QTL heritability. We also describe both how the power of linkage is attenuated by incomplete linkage and incomplete marker information and how the power of association is attenuated by incomplete linkage disequilibrium.