Faculty of Engineering, Department of Computer Engineering, University of Gonabad, Gonabad, Iran.
Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg im Breisgau, Germany.
PLoS One. 2020 Oct 29;15(10):e0241291. doi: 10.1371/journal.pone.0241291. eCollection 2020.
Decreasing the cost of high-throughput DNA sequencing technologies, provides a huge amount of data that enables researchers to determine haplotypes for diploid and polyploid organisms. Although various methods have been developed to reconstruct haplotypes in diploid form, their accuracy is still a challenging task. Also, most of the current methods cannot be applied to polyploid form. In this paper, an iterative method is proposed, which employs hypergraph to reconstruct haplotype. The proposed method by utilizing chaotic viewpoint can enhance the obtained haplotypes. For this purpose, a haplotype set was randomly generated as an initial estimate, and its consistency with the input fragments was described by constructing a weighted hypergraph. Partitioning the hypergraph specifies those positions in the haplotype set that need to be corrected. This procedure is repeated until no further improvement could be achieved. Each element of the finalized haplotype set is mapped to a line by chaos game representation, and a coordinate series is defined based on the position of mapped points. Then, some positions with low qualities can be assessed by applying a local projection. Experimental results on both simulated and real datasets demonstrate that this method outperforms most other approaches, and is promising to perform the haplotype assembly.
降低高通量 DNA 测序技术的成本，提供了大量的数据，使研究人员能够确定二倍体和多倍体生物的单倍型。虽然已经开发了各种方法来重建二倍体形式的单倍型，但它们的准确性仍然是一个具有挑战性的任务。此外，目前的大多数方法都不能应用于多倍体形式。在本文中，提出了一种迭代方法，该方法利用超图来重建单倍型。所提出的方法通过利用混沌观点，可以增强获得的单倍型。为此，随机生成一组单倍型作为初始估计，并通过构建加权超图来描述其与输入片段的一致性。超图的分区指定了单倍型集中需要校正的那些位置。此过程重复进行，直到无法进一步改进为止。最终的单倍型集中的每个元素都通过混沌游戏表示映射到一条线上，并根据映射点的位置定义一个坐标序列。然后，可以通过应用局部投影来评估质量较低的某些位置。在模拟和真实数据集上的实验结果表明，该方法优于大多数其他方法，有望进行单倍型组装。
