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A Practical Comparison of De Novo Genome Assembly Software Tools for Next-Generation Sequencing Technologies

机译:De Novo基因组组装软件工具用于下一代测序技术的实用比较

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摘要

The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.
机译:下一代测序技术的出现伴随着许多全基因组序列装配方法和软件的开发,尤其是从头片段装配。由于对这些软件工具的适用性和性能的了解不多,因此选择合适的汇编程序将成为一项艰巨的任务。在这里,我们提供每个程序的适应性信息,然后最重要的是,将八个不同工具的性能与Solexa测序平台的八组模拟数据集进行比较。考虑到计算时间,最大随机存取存储器(RAM)占用率,汇编精度和完整性,我们的研究表明,基于字符串的汇编器,重叠布局共识(OLC)汇编器非常适合于小读和长读基因组。对于短读超过亿的大型数据集,基于De Bruijn图的汇编器会更合适。在软件实现方面,基于字符串的汇编程序优于基于图形的汇编程序,其中SOAPdenovo对于创建配置文件而言很复杂。我们的比较研究将帮助研究人员选择合适的组装工,并为改进现有组装工或开发新型组装工提供重要信息。

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