The de Bruijn Graph algorithm (DBG) as one of the cornerstones algorithms in short read assembly has extended with the rapid advancement of the Next Generation Sequencing (NGS) technologies and low-cost production of millions of high-quality short reads. Erroneous reads, non-uniform coverage, and genomic repeats are three major problems that influence the performance of short read assemblers. To encounter these problems, the iterative DBG algorithm applies multiple k-mers instead of a single k-mer, by iterating the DBG graph over a range of k-mer sizes from the minimum to the maximum. However, the iteration paradigm of iterative DBG deals with complex graphs from the beginning of the algorithm and therefore, causes more potential errors and computational time for resolving various unreal branches. In this research, we propose the Reverse Modified Iterative DBG graph (named RMI-DBG) for short read assembly. RMI-DBG utilizes the DBG algorithm and String graph to achieve the advantages of both algorithms. We present that RMI-DBG performs faster with comparable results in comparison to iterative DBG. Additionally, the quality of the proposed algorithm in terms of continuity and accuracy is evaluated with some commonly-used assemblers via several real datasets of the GAGE-B benchmark.

中文翻译：

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RMI-DBG 算法：短读基因组组装中更敏捷的迭代 de Bruijn 图算法

de Bruijn Graph 算法 (DBG) 作为短读组装的基石算法之一，随着下一代测序 (NGS) 技术的快速发展和数百万高质量短读的低成本生产而得到扩展。错误读取、不均匀覆盖和基因组重复是影响短读取组装器性能的三个主要问题。针对这些问题，迭代 DBG 算法应用了多个ķ-mers 而不是单个ķ-mer，通过在一定范围内迭代 DBG 图ķ-mer 大小从最小值到最大值。然而，迭代 DBG 的迭代范式从算法一开始就处理复杂的图，因此会导致更多的潜在错误和计算时间来解决各种虚幻分支。在这项研究中，我们提出了用于短读组装的反向修改迭代 DBG 图（命名为 RMI-DBG）。RMI-DBG 利用 DBG 算法和字符串图来实现两种算法的优点。我们提出，与迭代 DBG 相比，RMI-DBG 的执行速度更快，结果相当。此外，通过 GAGE-B 基准测试的几个真实数据集，使用一些常用的汇编程序评估了所提出算法在连续性和准确性方面的质量。