基于最小误差修正的多单倍型重构启发式算法的扩展

M. Hossain, A. Abdullah, P. C. Shill
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引用次数: 1

摘要

人类DNA由每条染色体的两个副本组成。单倍型组装问题侧重于从基因组序列的对齐片段中重建两组单倍型(染色体)。像水稻、小麦和香蕉这样的植物由两条以上的染色体组成,这意味着多个单倍型。重建多个单倍型已经成为一个热门的研究方向。从多倍体基因组中重建多个单倍型已经开发了几种模型。计算挑战仍然吸引着研究人员。我们正在扩展单个单倍型的启发式算法,以便为多倍体生物体重建多个单倍型,从而使DNA读取组之间的错误数量最小。我们正在使用一个度量来确定不适合任何构建组的读取或片段,并导致创建一个新组。在真实数据和模拟数据上的实验结果以及与现有模型的比较表明,我们的模型可以在较少的计算时间和内存使用下重构多个组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Extension of Heuristic Algorithm for Reconstructing Multiple Haplotypes with Minimum Error Correction
Human DNA consists of two copies of each chromosome. The haplotype assembly problem focuses on the reconstruction of two sets of haplotypes (chromosomes) from aligned fragments of the genome sequence. Plants like rice, wheat, and banana consist of more than two chromosomes which mean multiple haplotypes. Reconstructing multiple haplotypes has become an intense research interest. There are several models that have been developed for the reconstruction of multiple haplotypes from a polyploid genome. The computational challenge still attracts researchers. We are extending the heuristic algorithm for individual haplotyping in order to reconstruct multiple haplotypes for a polyploid organism so that the number of errors among the groups of DNA reads is minimum. We are using a metric that determines the read or fragment which fits for none of the constructed groups and it results in the creation of a new group. Experimental results on real and simulated data and their comparison with existing models show that our model can reconstruct multiple groups with less computational time and memory usage.
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