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HMEC: A Heuristic Algorithm for Individual Haplotyping with Minimum Error Correction

机译:HMEC:具有最小误差校正的个人单体型启发式算法

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摘要

Haplotype is a pattern of single nucleotide polymorphisms (SNPs) on a single chromosome. Constructing a pair of haplotypes from aligned and overlapping but intermixed and erroneous fragments of the chromosomal sequences is a nontrivial problem. Minimum error correction approach aims to minimize the number of errors to be corrected so that the pair of haplotypes can be constructed through consensus of the fragments. We give a heuristic algorithm (HMEC) that searches through alternative solutions using a gain measure and stops whenever no better solution can be achieved. Time complexity of each iteration is O(m 3 k) for an m × k SNP matrix where m and k are the number of fragments (number of rows) and number of SNP sites (number of columns), respectively, in an SNP matrix. Alternative gain measure is also given to reduce running time. We have compared our algorithm with other methods in terms of accuracy and running time on both simulated and real data, and our extensive experimental results indicate the superiority of our algorithm over others.
机译:单倍型是在单个染色体上的单核苷酸多态性(SNP)的模式。从染色体序列的对齐和重叠但相互混合和错误的片段构建一对单倍型是一个不小的问题。最小错误校正方法旨在最小化要校正的错误数,以便可以通过片段的共有来构建一对单倍型。我们给出了一种启发式算法(HMEC),该算法使用增益度量搜索替代解决方案,并在无法获得更好的解决方案时停止。对于m×k SNP矩阵,每次迭代的时间复杂度为O(m 3 k),其中m和k是片段数(行数)和SNP位点数(列数)分别在SNP矩阵中。还提供了替代增益措施以减少运行时间。我们已经在模拟和真实数据的准确性和运行时间方面将我们的算法与其他方法进行了比较,我们广泛的实验结果表明了我们的算法在其他方面的优越性。

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