A constrained-likelihood approach to marker-trait association studies
A constrained-likelihood approach to marker-trait association studies
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DOI：
10.1086/497434
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发表时间：
2005-11-01
影响因子：
9.8
通讯作者：
Sheffield, VC
中科院分区：
文献类型：
--
作者：
Wang, K;Sheffield, VC
标记-性状关联分析是检测遗传性状变异的重要统计工具。在这样的分析中，通常指定基因型的平均遗传效应的分析模型。例如，疾病等位基因对性状的影响通常被指定为显性、隐性、加性或倍增。虽然这种基于模型的方法在正确指定分析模型时功能强大，但有时发现在指定模型不正确时功能较低。我们介绍了一种方法，不需要指定一个特定的遗传模型。这种方法是建立在一个约束的最大似然法，其中杂合基因型的平均遗传效应需要不超过两个纯合基因型。似然比统计量的渐近分布推导出两种特殊情况。仿真研究表明，这种新的方法具有权力的分析模型时，正确指定的基于模型的方法。这种方法一次使用一个标记（即，它是单标记分析）。然而，鉴于最新的发现，单倍型分析的强大的推理程序可以从单标记分析，我们希望这种方法是有用的单倍型分析。
Marker-trait association analysis is an important statistical tool for detecting DNA variants responsible for genetic traits. In such analyses, an analysis model of the mean genetic effects of the genotypes is often specified. For instance, the effect of the disease allele on the trait is often specified to be dominant, recessive, additive, or multiplicative. Although this model-based approach is powerful when the analysis model is correctly specified, it has been found to have low power sometimes when the specified model is incorrect. We introduce an approach that does not require the specification of a particular genetic model. This approach is built upon a constrained maximum likelihood in which the mean genetic effect of the heterozygous genotype is required to not exceed those of the two homozygous genotypes. The asymptotic distribution of the likelihood-ratio statistic is derived for two special cases. A simulation study suggests that this new approach has power comparable to that of the model-based method when the analysis model is correctly specified. This approach uses one marker at a time (i.e., it is a single-marker analysis). However, given the latest findings that powerful inferential procedures for haplotype analyses can be constructed from single-marker analyses, we expect this approach to be useful for haplotype analyses.