Introducing DOTUR, a Computer Program for Defining Operational Taxonomic Units and Estimating Species Richness.

阅读量:

226

作者:

SchlossD PatrickHandelsmanJo

展开

摘要:

Although copious qualitative information describes the members of the diverse microbial communities on Earth, statistical approaches for quantifying and comparing the numbers and compositions of lineages in communities are lacking. We present a method that addresses the challenge of assigning sequences to operational taxonomic units (OTUs) based on the genetic distances between sequences. We developed a computer program, DOTUR, which assigns sequences to OTUs by using either the furthest, average, or nearest neighbor algorithm for each distance level. DOTUR uses the frequency at which each OTU is observed to construct rarefaction and collector's curves for various measures of richness and diversity. We analyzed 16S rRNA gene libraries derived from Scottish and Amazonian soils and the Sargasso Sea with DOTUR, which assigned sequences to OTUs rapidly and reliably based on the genetic distances between sequences and identified previous inconsistencies and errors in assigning sequences to OTUs. An analysis of the two 16S rRNA gene libraries from soil demonstrated that they do not contain enough sequences to support a claim that they contain different numbers of bacterial lineages with statistical confidence (P > 0.05), nor do they contain enough sequences to provide a robust estimate of species richness when an OTU is defined as containing sequences that are no more than 3% different from each other. In contrast, the richness of OTUs at the 3% level in the Sargasso Sea collection began to plateau after the sampling of 690 sequences. We anticipate that an equivalent extent of sampling for soil would require sampling more than 10,000 sequences, almost 100 times the size of typical sequence collections obtained from soil.

展开

DOI:

10.1128/AEM.71.3.1501.1506.2005

被引量:

4498

年份:

2005

通过文献互助平台发起求助,成功后即可免费获取论文全文。

相似文献

参考文献

引证文献

引用走势

2010
被引量:708

站内活动

辅助模式

0

引用

文献可以批量引用啦~
欢迎点我试用!

关于我们

百度学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们保持学习的态度,不忘初心,砥砺前行。
了解更多>>

友情链接

百度云百度翻译

联系我们

合作与服务

期刊合作 图书馆合作 下载产品手册

©2025 Baidu 百度学术声明 使用百度前必读

引用