MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences
Identifieur interne : 000183 ( Pmc/Checkpoint ); précédent : 000182; suivant : 000184MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences
Auteurs : Chengwei Luo [États-Unis] ; Luis M. Rodriguez-R [États-Unis] ; Konstantinos T. Konstantinidis [États-Unis]Source :
- Nucleic Acids Research [ 0305-1048 ] ; 2014.
Abstract
Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on
Url:
DOI: 10.1093/nar/gku169
PubMed: 24589583
PubMed Central: 4005636
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on <italic>in silico</italic>
generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ∼10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant <italic>in situ</italic>
such as members of the <italic>Prevotella</italic>
genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.</p>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Nucleic Acids Res</journal-id>
<journal-id journal-id-type="iso-abbrev">Nucleic Acids Res</journal-id>
<journal-id journal-id-type="publisher-id">nar</journal-id>
<journal-id journal-id-type="hwp">nar</journal-id>
<journal-title-group><journal-title>Nucleic Acids Research</journal-title>
</journal-title-group>
<issn pub-type="ppub">0305-1048</issn>
<issn pub-type="epub">1362-4962</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">24589583</article-id>
<article-id pub-id-type="pmc">4005636</article-id>
<article-id pub-id-type="doi">10.1093/nar/gku169</article-id>
<article-id pub-id-type="publisher-id">gku169</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Methods Online</subject>
</subj-group>
</article-categories>
<title-group><article-title>MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Luo</surname>
<given-names>Chengwei</given-names>
</name>
<xref ref-type="aff" rid="gku169-AFF1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="gku169-AFF1"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Rodriguez-R</surname>
<given-names>Luis M.</given-names>
</name>
<xref ref-type="aff" rid="gku169-AFF1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="gku169-AFF1"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Konstantinidis</surname>
<given-names>Konstantinos T.</given-names>
</name>
<xref ref-type="aff" rid="gku169-AFF1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="gku169-AFF1"><sup>2</sup>
</xref>
<xref ref-type="corresp" rid="gku169-COR1">*</xref>
</contrib>
<aff id="gku169-AFF1"><sup>1</sup>
Centre for Bioinformatics and Computational Genomics, and School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA and<sup>2</sup>
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA</aff>
</contrib-group>
<author-notes><corresp id="gku169-COR1">*To whom correspondence should be addressed. Tel: <phone>+1 404 385 3628</phone>
; Fax: <fax>+1 404 894 8266</fax>
; Email: <email>kostas@ce.gatech.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><month>4</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="epub"><day>3</day>
<month>3</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>3</day>
<month>3</month>
<year>2014</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>42</volume>
<issue>8</issue>
<fpage>e73</fpage>
<lpage>e73</lpage>
<history><date date-type="received"><day>30</day>
<month>9</month>
<year>2013</year>
</date>
<date date-type="rev-recd"><day>9</day>
<month>2</month>
<year>2014</year>
</date>
<date date-type="accepted"><day>10</day>
<month>2</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-statement>© The Author(s) 2014. Published by Oxford University Press.</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link>
), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<abstract><p>Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on <italic>in silico</italic>
generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ∼10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant <italic>in situ</italic>
such as members of the <italic>Prevotella</italic>
genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.</p>
</abstract>
<counts><page-count count="12"></page-count>
</counts>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Géorgie (États-Unis)</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Luo, Chengwei" sort="Luo, Chengwei" uniqKey="Luo C" first="Chengwei" last="Luo">Chengwei Luo</name>
</region>
<name sortKey="Konstantinidis, Konstantinos T" sort="Konstantinidis, Konstantinos T" uniqKey="Konstantinidis K" first="Konstantinos T." last="Konstantinidis">Konstantinos T. Konstantinidis</name>
<name sortKey="Konstantinidis, Konstantinos T" sort="Konstantinidis, Konstantinos T" uniqKey="Konstantinidis K" first="Konstantinos T." last="Konstantinidis">Konstantinos T. Konstantinidis</name>
<name sortKey="Luo, Chengwei" sort="Luo, Chengwei" uniqKey="Luo C" first="Chengwei" last="Luo">Chengwei Luo</name>
<name sortKey="Rodriguez R, Luis M" sort="Rodriguez R, Luis M" uniqKey="Rodriguez R L" first="Luis M." last="Rodriguez-R">Luis M. Rodriguez-R</name>
<name sortKey="Rodriguez R, Luis M" sort="Rodriguez R, Luis M" uniqKey="Rodriguez R L" first="Luis M." last="Rodriguez-R">Luis M. Rodriguez-R</name>
</country>
</tree>
</affiliations>
</record>
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