Evolutionary-based grouping of haplotypes in association analysis
Evolutionary-based grouping of haplotypes in association analysis
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DOI：
10.1002/gepi.20063
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发表时间：
2005-04-01
影响因子：
2.1
通讯作者：
Tzeng, JY
中科院分区：
文献类型：
--
作者：
Tzeng, JY
单倍型比单个SNP的基因型包含更多关于潜在多态性的信息，并且被认为是关联分析中更有信息量的数据格式。单倍型建模需要高度的自由度，这可能会降低功效并限制模型纳入其他复杂效应（如基因-基因相互作用）的能力。即使在单倍型块内，高自由度仍然是一个问题，除非人们选择丢弃罕见的单倍型。为了提高单倍型分析的效率和能力，我们采用进化概念的分支分析，并提出了一个分组算法，以集群罕见的单倍型，以相应的祖先单倍型。该算法通过使用建立在香农信息内容上的标准来保留常见的单倍型来确定聚类基础。每个单倍型，然后分配到其适当的集群概率根据分支关系。通过该算法，我们进行关联分析的基础上组的单倍型。模拟结果表明，与使用原始单倍型或截断单倍型分布的测试相比，对单倍型簇进行测试的功率增加。(c)2005 Wiley-Liss，Inc.
Haplotypes incorporate more information about the underlying polymorphisms than do genotypes for individual SNPs, and are considered as a more informative format of data in association analysis. To model haplotypes requires high degrees of freedom, which could decrease power and limit a model's capacity to incorporate other complex effects, such as gene-gene interactions. Even within haplotype blocks, high degrees of freedom are still a concern unless one chooses to discard rare haplotypes. To increase the efficiency and power of haplotype analysis, we adapt the evolutionary concepts of cladistic analyses and propose a grouping algorithm to cluster rare haplotypes to the corresponding ancestral haplotypes. The algorithm determines the cluster bases by preserving common haplotypes using a criterion built on the Shannon information content. Each haplotype is then assigned to its appropriate clusters probabilistically according to the cladistic relationship. Through this algorithm, we perform association analysis based on groups of haplotypes. Simulation results indicate power increases for performing tests on the haplotype clusters when compared to tests using original haplotypes or the truncated haplotype distribution. (c) 2005 Wiley-Liss, Inc.