Algorithms for inferring haplotypes
Algorithms for inferring haplotypes
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DOI：
10.1002/gepi.20024
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发表时间：
2004-12-01
影响因子：
2.1
通讯作者：
Niu, TH
中科院分区：
文献类型：
--
作者：
Niu, TH
二倍体生物体中的单倍型相位信息提供了关于人类进化史的有价值的信息，并且可能导致开发更有效的策略来识别增加对人类疾病的易感性的遗传变异。分子单体型分析方法是劳动密集型的，低通量的，并且非常昂贵。因此，基于正式统计理论的算法被证明对于单倍型重建非常有效且具有成本效益。本文综述了1）基于群体的单倍型推断方法：Clark算法、期望最大化（EM）算法、基于聚结的算法（伪Gibbs采样器和完美/不完美遗传学）以及通过完全贝叶斯模型（Haplotyper）或EM（PLEM）实现的分割连接算法; 2）基于家族的单倍型推断方法; 3）基因型评分不确定性的处理（即，基因分型误差和原始二维基因型散点图）;和4）用于合并的DNA样品的单倍型推断方法。每种算法的优点和局限性进行了讨论。通过使用基于G6 PD基因和TNFRSF 5基因的经验数据的模拟，我证明了不同的算法对不同程度的群体差异和基因分型错误率具有不同程度的敏感性。未来单倍型重建的统计算法的发展将越来越多地依赖于基于组合数学、图形模型和机器学习的思想，随着人类HapMap的出现，它们将对群体遗传学和遗传流行病学产生深远的影响。Genet.肾上腺素(C)2004 Wiley-Liss，Inc.
Haplotype phase information in diploid organisms provides valuable information on human evolutionary history and may lead to the development of more efficient strategies to identify genetic variants that increase susceptibility to human diseases. Molecular haplotyping methods are labor-intensive, low-throughput, and very costly. Therefore, algorithms based on formal statistical theories were shown to be very effective and cost-efficient for haplotype reconstruction. This review covers 1) population-based haplotype inference methods: Clark's algorithm, expectation-maximization (EM) algorithm, coalescence-based algorithms (pseudo-Gibbs sampler and perfect/imperfect phylogeny), and partition-ligation algorithm implemented by a fully Bayesian model (Haplotyper) or by EM (PLEM); 2) family-based haplotype inference methods; 3) the handling of genotype scoring uncertainties (i.e., genotyping errors and raw two-dimensional genotype scatterplots) in inferring haplotypes; and 4) haplotype inference methods for pooled DNA samples. The advantages and limitations of each algorithm are discussed. By using simulations based on empirical data on the G6PD gene and TNFRSF5 gene, I demonstrate that different algorithms have different degrees of sensitivity to various extents of population diversities and genotyping error rates. Future development of statistical algorithms for addressing haplotype reconstruction will resort more and more to ideas based on combinatorial mathematics, graphical models, and machine learning, and they will have profound impacts on population genetics and genetic epidemiology with the advent of the human HapMap. Genet. Epiderniol. (C) 2004 Wiley-Liss, Inc.