Bayesian analysis of multilocus association in quantitative and qualitative traits
Bayesian analysis of multilocus association in quantitative and qualitative traits
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DOI：
10.1002/gepi.10257
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发表时间：
2003-09-01
影响因子：
2.1
通讯作者：
Sillanpää, MJ
中科院分区：
文献类型：
--
作者：
Kilpikari, R;Sillanpää, MJ
提出了一种基于贝叶斯模型的多位点定量和定性（二元）性状关联分析方法。该方法在候选标记中选择与性状相关的标记子集，同样适用于分析宽染色体片段（基因组扫描）和小候选区域。该方法可应用于缺失基因型数据的情况。性状位点的数量，它们的标记位置，以及它们的基因效应的大小（关联强度）都是同时估计的。参数的推理是基于它们的后验分布，通过马尔可夫链蒙特卡罗模拟得到。该方法的优点是：1)灵活地使用未知基因座的寡基因模型；2)将关联估计与模型选择联合进行；3)避免了多重测试问题，这通常会使基于关联测试的方法变得复杂。通过对两个模拟数据集的分析，验证了该方法的性能，并与多轨迹条件搜索方法进行了比较。我们还将该方法应用于囊性纤维化单倍型数据（双位点单倍型），其中基因位置已经确定。该方法以软件包的形式实现，该软件包以BAMA的名义免费用于研究目的。(C) 2003 Wiley-Liss, Inc。
A Bayesian model-based method for multilocus association analysis of quantitative and qualitative (binary) traits is presented. The method selects a trait-associated subset of markers among candidates, and is equally applicable for analyzing wide chromosomal segments (genome scans) and small candidate regions. The method can be applied in situations involving missing genotype data. The number of trait loci, their marker positions, and the magnitudes of their gene effects (strengths of association) are all estimated simultaneously. The inference of parameters is based on their posterior distributions, which are obtained through Markov chain Monte Carlo simulations. The strengths of the approach are: 1) flexible use of oligogenic models with unknown number of loci, 2) performing the estimation of association jointly with model selection, and 3) avoidance of the multiple testing problem, which typically complicates the approaches based on association testing. The performance of the method was tested and compared to the multilocus conditional search procedure by analyzing two simulated data sets. We also applied the method to cystic fibrosis haplotype data (two-locus haplotypes), where gene position has already been identified. The method is implemented as a software package, which is freely available for research purposes under the name BAMA. (C) 2003 Wiley-Liss, Inc.