2.50
Hdl Handle:
http://hdl.handle.net/10033/337182
Title:
Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.
Authors:
Dröge, J; Gregor, I; McHardy, A C
Abstract:
Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.
Affiliation:
Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany.
Citation:
Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods. 2014: Bioinformatics
Journal:
Bioinformatics (Oxford, England)
Issue Date:
10-Nov-2014
URI:
http://hdl.handle.net/10033/337182
DOI:
10.1093/bioinformatics/btu745
PubMed ID:
25388150
Type:
Article
ISSN:
1367-4811
Appears in Collections:
publications of the research group bioinformatics in infection research ([BRICS] BIFO)

Full metadata record

DC FieldValue Language
dc.contributor.authorDröge, Jen
dc.contributor.authorGregor, Ien
dc.contributor.authorMcHardy, A Cen
dc.date.accessioned2014-12-15T15:33:28Z-
dc.date.available2014-12-15T15:33:28Z-
dc.date.issued2014-11-10-
dc.identifier.citationTaxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods. 2014: Bioinformaticsen
dc.identifier.issn1367-4811-
dc.identifier.pmid25388150-
dc.identifier.doi10.1093/bioinformatics/btu745-
dc.identifier.urihttp://hdl.handle.net/10033/337182-
dc.description.abstractMetagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.en
dc.languageENG-
dc.titleTaxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.-
dc.typeArticleen
dc.contributor.departmentDepartment for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany.en
dc.identifier.journalBioinformatics (Oxford, England)en

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