【24h】

The Genome Assembly Model for Next-Generation Sequencing Data

机译:下一代测序数据的基因组装配模型

获取原文

摘要

At present, next-generation sequencing technology are quickly applied to every field of life science research. Per base has higher coverage and lower cost. Shorter reads and higher error rates from these new instruments necessitate the development of new algorithm and software[1]. We describe an assembly algorithm for next-generation sequencing data. The algorithms developed to solve this problem are based on de Bruijn graph, greedy strategy and quicksort. We explain the algorithm and present the results of assembling a bacterial artificial chromosome (BAC). The value of scaffold N50 is 71613, and N90 is 157742. And the final running time is 20.796 seconds. The value of N50 and N90 reflect the ability of scaffold sequence covering reference genome, the bigger the better. Therefore, the algorithm seems to be good for solving short reads assembly problem.
机译:目前,迅速应用下一代测序技术对生命科学研究的每个领域。每个碱度具有更高的覆盖率和更低的成本。这些新仪器的较短读取和更高的错误率需要开发新算法和软件[1]。我们描述了一种用于下一代测序数据的装配算法。开发解决此问题的算法基于De Bruijn图表,贪婪的策略和Quicksort。我们解释了算法,并呈现组装细菌人工染色体(BAC)的结果。支架N50的值为71613,N90为157742.并且最终运行时间为20.796秒。 N50和N90的值反映了支架序列覆盖参考基因组的能力,更大更好。因此,该算法似乎有利于解决短读装配问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号