Finding associations in dense genetic maps: A genetic algorithm approach
Finding associations in dense genetic maps: A genetic algorithm approach
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DOI：
10.1159/000088845
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发表时间：
2005-01-01
期刊：
影响因子：
1.8
通讯作者：
Farrall, M
中科院分区：
文献类型：
--
作者：
Clark, TG;De Iorio, M;Farrall, M
大规模关联研究有望发现人类常见疾病的遗传基础。这些研究将包括大量的个体，以及大量的遗传标记，如单核苷酸多态性（SNP）。数据的潜在规模和由此产生的模型空间需要开发有效的方法来解开密集遗传图谱中表型和SNP之间的关联。我们的方法使用遗传算法（GA）来构建逻辑树包括布尔表达式涉及字符串或块的SNP。逻辑树的这些块或节点由处于高连锁不平衡（LD）的SNP组成，即，由于进化过程而彼此高度相关的SNP。在我们的GA的每一代，人口的逻辑树模型进行修改，使用选择，交叉和突变移动。在贝叶斯回归框架中，基于边缘似然的适应度函数为下一代选择逻辑树。突变和交叉移动使用LD措施来建议对树的更改，并促进通过模型空间的移动。我们证明了我们的方法和灵活性的逻辑树结构与可变节点长度的模拟数据从合并模型，以及从候选基因研究的定量遗传变异的数据。版权所有（c）2005 S. Karger AG，巴塞尔。
Large-scale association studies hold promise for discovering the genetic basis of common human disease. These studies will consist of a large number of individuals, as well as large number of genetic markers, such as single nucleotide polymorphisms ( SNPs). The potential size of the data and the resulting model space require the development of efficient methodology to unravel associations between phenotypes and SNPs in dense genetic maps. Our approach uses a genetic algorithm ( GA) to construct logic trees consisting of Boolean expressions involving strings or blocks of SNPs. These blocks or nodes of the logic trees consist of SNPs in high linkage disequilibrium ( LD), that is, SNPs that are highly correlated with each other due to evolutionary processes. At each generation of our GA, a population of logic tree models is modified using selection, cross-over and mutation moves. Logic trees are selected for the next generation using a fitness function based on the marginal likelihood in a Bayesian regression frame-work. Mutation and cross-over moves use LD measures to propose changes to the trees, and facilitate the movement through the model space. We demonstrate our method and the flexibility of logic tree structure with variable nodal lengths on simulated data from a coalescent model, as well as data from a candidate gene study of quantitative genetic variation. Copyright (c) 2005 S. Karger AG, Basel.