Application of Bayesian spatial statistical methods to analysis of haplotypes effects and gene mapping.
Application of Bayesian spatial statistical methods to analysis of haplotypes effects and gene mapping.
复制标题
应用贝叶斯空间统计方法分析单倍型效应和基因作图。
DOI：
10.1002/gepi.10251
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Thomas,Duncan
中科院分区：
文献类型：
--
作者：
Molitor,John;Marjoram,Paul;Thomas,Duncan
We propose a method to analyze haplotype effects using ideas derived from Bayesian spatial statistics. We assume that two haplotypes that are similar to one another in structure are likely to have similar risks, and define a distance metric to specify the appropriate level of closeness between the two haplotypes. Through the choice of distance metric, varying levels of population genetics theory can be incorporated into the modeling process, including some that allow estimation of the location of the disease causing mutation(s). This location can be estimated, along with the other parameters of the model, using Markov chain Monte Carlo (MCMC) estimation methods. We demonstrate the effectiveness of the model on two real datasets, a well‐known dataset used to fine‐map the gene for cystic fibrosis, and one used to localize the gene for Friedreich's ataxia.Genet Epidemiol25:95–105, 2003. © 2003 Wiley‐Liss, Inc.
