用于OTU提取和系统发育分析的超快生物信息学工具
  • HmmUFOtu是一个基于隐马尔科夫模型的超快OTU工具,由两个核心算法组成:banded-HMM比对和局部系统发育放置算法;
  • 可用于从16S rRNA基因测序数据提取OTU及进行OTU系统发育分析的任务;
  • 在比对的准确性上仅比blastn低3.5%,但速度要快约300倍;
  • 在系统发育分析时比Pplacer等更灵敏、准确,速度上则要快30倍;
  • 由于该工具是依次分析测序的短序列,在处理大数据集时很容易借助多线程提高性能,而内存占用却保持稳定。
主编推荐语
高春辉
从菌群16S rRNA测序数据中提取OTU和对这些OTU进行系统发育分析是宏基因组学研究中的常见任务,而现有的方法如QIIME事实上在准确性和效能等方面都有一些缺陷。Genome Biology发表的这篇文章介绍了一种新的、更快更准确的生物信息学工具,弥补了现有工具的不足。值得专业人士参考。
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Genome Biology [IF:10.806]

HmmUFOtu: An HMM and phylogenetic placement based ultra-fast taxonomic assignment and OTU picking tool for microbiome amplicon sequencing studies

HmmUFOtu:一个基于HMM和系统发育树定位方法快速对菌群扩增子测序数据进行分类学分配和OTU挑选的工具

10.1186/s13059-018-1450-0

2018-06-27, Article

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Culture-independent analysis of microbial communities frequently relies on amplification and sequencing of the prokaryotic 16S ribosomal RNA gene. Typical analysis pipelines group sequences into operational taxonomic units (OTUs) to infer taxonomic and phylogenetic relationships. Here, we present HmmUFOtu, a novel tool for processing microbiome amplicon sequencing data, which performs rapid per-read phylogenetic placement, followed by phylogenetically informed clustering into OTUs and taxonomy assignment. Compared to standard pipelines, HmmUFOtu more accurately and reliably recapitulates microbial community diversity and composition in simulated and real datasets without relying on heuristics or sacrificing speed or accuracy.

First Authors:
Qi Zheng

Correspondence Authors:
Qi Zheng,Elizabeth A Grice

All Authors:
Qi Zheng,Casey Bartow-McKenney,Jacquelyn S Meisel,Elizabeth A Grice

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