Haplotype inference by maximum parsimony
Haplotype inference by maximum parsimony
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DOI：
10.1093/bioinformatics/btg239
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发表时间：
2003-09-22
期刊：
影响因子：
5.8
通讯作者：
Xu, Y
中科院分区：
文献类型：
--
作者：
Wang, LS;Xu, Y
动机：单倍型已经吸引了越来越多的关注，因为它们在许多精细分子遗传学数据的分析中很重要。由于通过实验方法直接测序单倍型既耗时又昂贵，因此基于基因样本推断单倍型的单倍型推断方法成为备受关注的替代方法。结果：(1)针对已有的单倍型推断的重要计算模型，设计并实现了一种算法。该模型找到了一组最小数量的单倍型来解释基因样本。(2)基于实际数据和仿真数据的计算结果，给出了该计算模型的有力支持。(3)利用我们的程序进行了对比研究，分析了该计算模型的优缺点。
Motivation: Haplotypes have been attracting increasing attention because of their importance in analysis of many fine-scale molecular-genetics data. Since direct sequencing of haplotype via experimental methods is both time-consuming and expensive, haplotype inference methods that infer haplotypes based on genotype samples become attractive alternatives.Results: (1) We design and implement an algorithm for an important computational model of haplotype inference that has been suggested before in several places. The model finds a set of minimum number of haplotypes that explains the genotype samples. (2) Strong supports of this computational model are given based on the computational results on both real data and simulation data. (3) We also did some comparative study to show the strength and weakness of this computational model using our program.