title: MetAmp: combining amplicon data from multiple markers for OTU analysis.
abstract: BACKGROUND
  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.
  
  
  METHODS
  MetAmp is available at http://izhbannikov.github.io/MetAmp/.
authors: Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.
authors: Ilya Y
authors: IY
authors: Zhbannikov
authors: 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.
authors: James A
authors: JA
authors: Foster
mesh_terms: D000465:Algorithms; D002965:Classification / Q000379:methods; D005819:Genetic Markers; D006801:Humans; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012984:Software
chemical_list: D005819:Genetic Markers; D012336:RNA, Ribosomal, 16S
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