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De novo assembly methods for next generation sequencing data
  • 期刊名称:Tsinghua Science and Technology
  • 时间:2013.3.3
  • 页码:500-514
  • 分类:TP311[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术] TQ426.81[化学工程]
  • 作者机构:[1]School of Information Science and Engineering, Central South University, Changsha 410083, China., [2]Morehouse School of Medicine, Atlanta, GA 30310, USA., [3]Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
  • 相关基金:Acknowledgements This work was supported in part by the National Natural Science Foundation of China (Nos. 61232001, 61128006, and 61073036).
  • 相关项目:难解问题的核心化技术及其应用研究
中文摘要:

The recent breakthroughs in next-generation sequencing technologies, such as those of Roche 454,Illumina/Solexa, and ABI SOLID, have dramatically reduced the cost of producing short reads of the genome of new species. The huge volume of reads, along with short read length, high coverage, and sequencing errors, poses a great challenge to de novo genome assembly. However, the paired-end information provides a new solution to these problems. In this paper, we review and compare some current assembly tools, including Newbler, CAP3, Velvet,SOAPdenovo, AllPaths, Abyss, IDBA, PE-Assembly, and Telescoper. In general, we compare the seed extension and graph-based methods that use the overlap/lapout/consensus approach and the de Bruijn graph approach for assembly. At the end of the paper, we summarize these methods and discuss the future directions of genome assembly.

英文摘要:

The recent breakthroughs in next-generation sequencing technologies, such as those of Roche 454,Illumina/Solexa, and ABI SOLID, have dramatically reduced the cost of producing short reads of the genome of new species. The huge volume of reads, along with short read length, high coverage, and sequencing errors, poses a great challenge to de novo genome assembly. However, the paired-end information provides a new solution to these problems. In this paper, we review and compare some current assembly tools, including Newbler, CAP3, Velvet,SOAPdenovo, AllPaths, Abyss, IDBA, PE-Assembly, and Telescoper. In general, we compare the seed extension and graph-based methods that use the overlap/lapout/consensus approach and the de Bruijn graph approach for assembly. At the end of the paper, we summarize these methods and discuss the future directions of genome assembly.

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