Assessing and Improving Methods Used in Operational Taxonomic Unit-Based Approaches for 16S rRNA Gene Sequence Analysis
Assessing and Improving Methods Used in Operational Taxonomic Unit-Based Approaches for 16S rRNA Gene Sequence Analysis
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DOI：
10.1128/aem.02810-10
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发表时间：
2011-05-01
影响因子：
4.4
通讯作者：
Westcott, Sarah L.
中科院分区：
文献类型：
--
作者：
Schloss, Patrick D.;Westcott, Sarah L.
尽管技术进步使测序覆盖率提高了几个数量级，但微生物生态学家仍在努力解决如何解释 16S rRNA 基因所代表的遗传多样性的问题。两种广泛使用的方法根据序列与参考序列的相似性（即系统发育）或与群落中其他序列的相似性（即操作分类单位 [OTU]）将序列放入箱中。在本研究中，我们研究了与基于 OTU 的方法的解释和实施相关的三个问题。首先，我们确认了传统观点，即不可能创建一个准确的基于距离的阈值来定义分类级别，而是提倡基于共识的 OTU 分类方法。其次，使用独立于分类学的方法，我们表明平均邻居聚类算法比其他层次和启发式聚类算法产生更稳健的 OTU。第三，我们演示了在不牺牲 OTU 分配的鲁棒性的情况下减少形成 OTU 的计算负担的几个步骤。最后，通过混合这些解决方案，我们提出了一种新的启发式方法，它对 OTU 的鲁棒性影响最小，并显着减少了必要的时间和内存需求。快速准确地将序列分配给 OTU，然后获取这些 OTU 的分类信息的能力将极大地改进基于 OTU 的分析，并克服基于系统发育型的方法遇到的许多挑战。
In spite of technical advances that have provided increases in orders of magnitude in sequencing coverage, microbial ecologists still grapple with how to interpret the genetic diversity represented by the 16S rRNA gene. Two widely used approaches put sequences into bins based on either their similarity to reference sequences (i.e., phylotyping) or their similarity to other sequences in the community (i.e., operational taxonomic units [OTUs]). In the present study, we investigate three issues related to the interpretation and implementation of OTU-based methods. First, we confirm the conventional wisdom that it is impossible to create an accurate distance-based threshold for defining taxonomic levels and instead advocate for a consensus-based method of classifying OTUs. Second, using a taxonomic-independent approach, we show that the average neighbor clustering algorithm produces more robust OTUs than other hierarchical and heuristic clustering algorithms. Third, we demonstrate several steps to reduce the computational burden of forming OTUs without sacrificing the robustness of the OTU assignment. Finally, by blending these solutions, we propose a new heuristic that has a minimal effect on the robustness of OTUs and significantly reduces the necessary time and memory requirements. The ability to quickly and accurately assign sequences to OTUs and then obtain taxonomic information for those OTUs will greatly improve OTU-based analyses and overcome many of the challenges encountered with phylotype-based methods.