Extension of the Haseman-Elston method to multiple alleles and multiple loci: theory and practice for candidate genes.
Extension of the Haseman-Elston method to multiple alleles and multiple loci: theory and practice for candidate genes.
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Haseman-Elston 方法扩展到多个等位基因和多个基因座：候选基因的理论与实践。
DOI：
10.1046/j.1469-1809.1997.6130263.x
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发表时间：
1997
期刊：
影响因子：
--
通讯作者：
Guerra,R
中科院分区：
文献类型：
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作者：
Stoesz,MR;Cohen,JC;Mooser,V;Marcovina,S;Guerra,R
Haseman & Elston (1972) 兄弟姐妹对回归方法已用于检测和估计特定候选基因中等位基因变异对数量性状观测值的方差贡献。该程序是在具有单个双等位基因座的模型下开发的。这个假设对于几个已知的系统并不成立。在本文中，我们证明对于候选基因分析，Haseman-Elston 程序可以扩展到多个性状基因座的情况，每个性状基因座可能具有两个以上等位基因。比较单基因座与双基因座模型的模拟实验表明，拟合扩展回归方程保持了名义显着性水平，但检测性状变异关联的能力并没有通过包含额外的基因座而提高。这些结果表明，最初的提议在统计上对于违反基础遗传模型是稳健的。还讨论了与量化各个基因座的相对方差贡献相关的实际问题。给出了脂蛋白（a）和高密度脂蛋白胆固醇的扩展回归方程的应用以供说明。
The Haseman & Elston (1972) sibling‐pair regression method has been used to detect and estimate the variance contribution to observed values of a quantitative trait by allelic variation in specific candidate genes. The procedure was developed under a model with a single biallelic trait locus. This assumption does not hold for several known systems. In this paper we prove that for candidate gene analysis the Haseman–Elston procedure extends to the case of multiple trait loci, each possibly having more than two alleles. Simulation experiments comparing single‐locus to two‐locus models show that fitting the extended regression equations maintains nominal significance levels, but the power to detect linkage to trait variation is not improved by including additional loci. These results indicate that the original proposal is statistically robust to violations of the underlying genetic model. Practical issues associated with quantifying the relative variance contribution by individual loci are also discussed. Applications of the extended regression equations to lipoprotein(a) and high density lipoprotein cholesterol are given for illustration.