MetAmp：整合来自多个标记的扩增子数据用于OTU分析。

MetAmp: combining amplicon data from multiple markers for OTU analysis.

作者信息

Zhbannikov Ilya Y, Foster James A

机构信息

Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.

Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.

出版信息

Bioinformatics. 2015 Jun 1;31(11):1830-2. doi: 10.1093/bioinformatics/btv049. Epub 2015 Jan 27.

DOI:10.1093/bioinformatics/btv049

PMID:25630378

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4443678/

Abstract

MOTIVATION

We present a novel method and corresponding application, MetAmp, to combine amplicon data from multiple genomic markers into Operational Taxonomic Units (OTUs) for microbial community analysis, calibrating the markers using data from known microbial genomes. When amplicons for multiple markers such as the 16S rRNA gene hypervariable regions are available, MetAmp improves the accuracy of OTU-based methods for characterizing bacterial composition and community structure. MetAmp works best with at least three markers, and is applicable to non-bacterial analyses and to non 16S markers. Our application and testing have been limited to 16S analysis of microbial communities.

RESULTS

We clustered standard test sequences derived from the Human Microbiome Mock Community test sets and compared MetAmp and other tools with respect to their ability to recover OTUs for these benchmark bacterial communities. MetAmp compared favorably to QIIME, UPARSE and Mothur using amplicons from one, two, and three markers.

AVAILABILITY AND IMPLEMENTATION

MetAmp is available at http://izhbannikov.github.io/MetAmp/.

摘要

动机

我们提出了一种新颖的方法及相应应用程序MetAmp，用于将来自多个基因组标记的扩增子数据组合成操作分类单元（OTU）以进行微生物群落分析，并使用已知微生物基因组的数据对标记进行校准。当有多个标记（如16S rRNA基因高变区）的扩增子时，MetAmp可提高基于OTU的方法在表征细菌组成和群落结构方面的准确性。MetAmp在至少有三个标记时效果最佳，并且适用于非细菌分析以及非16S标记。我们的应用和测试仅限于微生物群落的16S分析。