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GiRaF: robust, computational identification of influenza reassortments via graph mining

Identifieur interne : 000A33 ( Pmc/Curation ); précédent : 000A32; suivant : 000A34

GiRaF: robust, computational identification of influenza reassortments via graph mining

Auteurs : Niranjan Nagarajan ; Carl Kingsford [États-Unis]

Source :

RBID : PMC:3064795

Abstract

Reassortments in the influenza virus—a process where strains exchange genetic segments—have been implicated in two out of three pandemics of the 20th century as well as the 2009 H1N1 outbreak. While advances in sequencing have led to an explosion in the number of whole-genome sequences that are available, an understanding of the rate and distribution of reassortments and their role in viral evolution is still lacking. An important factor in this is the paucity of automated tools for confident identification of reassortments from sequence data due to the challenges of analyzing large, uncertain viral phylogenies. We describe here a novel computational method, called GiRaF (Graph-incompatibility-based Reassortment Finder), that robustly identifies reassortments in a fully automated fashion while accounting for uncertainties in the inferred phylogenies. The algorithms behind GiRaF search large collections of Markov chain Monte Carlo (MCMC)-sampled trees for groups of incompatible splits using a fast biclique enumeration algorithm coupled with several statistical tests to identify sets of taxa with differential phylogenetic placement. GiRaF correctly finds known reassortments in human, avian, and swine influenza populations, including the evolutionary events that led to the recent ‘swine flu’ outbreak. GiRaF also identifies several previously unreported reassortments via whole-genome studies to catalog events in H5N1 and swine influenza isolates.


Url:
DOI: 10.1093/nar/gkq1232
PubMed: 21177643
PubMed Central: 3064795

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Niranjan Nagarajan
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<wicri:noCountry code="subfield">Singapore-127726</wicri:noCountry>
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Le document en format XML

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<p>Reassortments in the influenza virus—a process where strains exchange genetic segments—have been implicated in two out of three pandemics of the 20th century as well as the 2009 H1N1 outbreak. While advances in sequencing have led to an explosion in the number of whole-genome sequences that are available, an understanding of the rate and distribution of reassortments and their role in viral evolution is still lacking. An important factor in this is the paucity of automated tools for confident identification of reassortments from sequence data due to the challenges of analyzing large, uncertain viral phylogenies. We describe here a novel computational method, called GiRaF (Graph-incompatibility-based Reassortment Finder), that robustly identifies reassortments in a fully automated fashion while accounting for uncertainties in the inferred phylogenies. The algorithms behind GiRaF search large collections of Markov chain Monte Carlo (MCMC)-sampled trees for groups of incompatible splits using a fast biclique enumeration algorithm coupled with several statistical tests to identify sets of taxa with differential phylogenetic placement. GiRaF correctly finds known reassortments in human, avian, and swine influenza populations, including the evolutionary events that led to the recent ‘swine flu’ outbreak. GiRaF also identifies several previously unreported reassortments via whole-genome studies to catalog events in H5N1 and swine influenza isolates.</p>
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<name sortKey="Amonsin, A" uniqKey="Amonsin A">A Amonsin</name>
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<name sortKey="Sreta, D" uniqKey="Sreta D">D Sreta</name>
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<name sortKey="Bunpong, N" uniqKey="Bunpong N">N Bunpong</name>
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<name sortKey="Luo, F" uniqKey="Luo F">F Luo</name>
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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="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">21177643</article-id>
<article-id pub-id-type="pmc">3064795</article-id>
<article-id pub-id-type="doi">10.1093/nar/gkq1232</article-id>
<article-id pub-id-type="publisher-id">gkq1232</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Methods Online</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>GiRaF: robust, computational identification of influenza reassortments via graph mining</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Nagarajan</surname>
<given-names>Niranjan</given-names>
</name>
<xref ref-type="aff" rid="AFF1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="COR1">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kingsford</surname>
<given-names>Carl</given-names>
</name>
<xref ref-type="aff" rid="AFF1">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="AFF1">
<sup>3</sup>
</xref>
</contrib>
</contrib-group>
<aff id="AFF1">
<sup>1</sup>
Computational and Mathematical Biology, Genome Institute of Singapore, Singapore-127726,
<sup>2</sup>
Center for Bioinformatics and Computational Biology and
<sup>3</sup>
Department of Computer Science, University of Maryland, College Park, MD 20742, USA</aff>
<author-notes>
<corresp id="COR1">*To whom correspondence should be addressed. Tel:
<phone>+65 6808 8071</phone>
; Fax:
<fax>+65 6808 9058</fax>
; Email:
<email>nagarajann@gis.a-star.edu.sg</email>
</corresp>
</author-notes>
<pmc-comment>For NAR both ppub and collection dates generated for PMC processing 1/27/05 beck</pmc-comment>
<pub-date pub-type="collection">
<month>3</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="ppub">
<month>3</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="epub">
<day>21</day>
<month>12</month>
<year>2010</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>21</day>
<month>12</month>
<year>2010</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the . </pmc-comment>
<volume>39</volume>
<issue>6</issue>
<fpage>e34</fpage>
<lpage>e34</lpage>
<history>
<date date-type="received">
<day>6</day>
<month>8</month>
<year>2010</year>
</date>
<date date-type="rev-recd">
<day>8</day>
<month>11</month>
<year>2010</year>
</date>
<date date-type="accepted">
<day>13</day>
<month>11</month>
<year>2010</year>
</date>
</history>
<permissions>
<copyright-statement>© The Author(s) 2010. Published by Oxford University Press.</copyright-statement>
<copyright-year>2010</copyright-year>
<license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by-nc/2.5">
<license-p>
<pmc-comment>CREATIVE COMMONS</pmc-comment>
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/2.5">http://creativecommons.org/licenses/by-nc/2.5</ext-link>
), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<abstract>
<p>Reassortments in the influenza virus—a process where strains exchange genetic segments—have been implicated in two out of three pandemics of the 20th century as well as the 2009 H1N1 outbreak. While advances in sequencing have led to an explosion in the number of whole-genome sequences that are available, an understanding of the rate and distribution of reassortments and their role in viral evolution is still lacking. An important factor in this is the paucity of automated tools for confident identification of reassortments from sequence data due to the challenges of analyzing large, uncertain viral phylogenies. We describe here a novel computational method, called GiRaF (Graph-incompatibility-based Reassortment Finder), that robustly identifies reassortments in a fully automated fashion while accounting for uncertainties in the inferred phylogenies. The algorithms behind GiRaF search large collections of Markov chain Monte Carlo (MCMC)-sampled trees for groups of incompatible splits using a fast biclique enumeration algorithm coupled with several statistical tests to identify sets of taxa with differential phylogenetic placement. GiRaF correctly finds known reassortments in human, avian, and swine influenza populations, including the evolutionary events that led to the recent ‘swine flu’ outbreak. GiRaF also identifies several previously unreported reassortments via whole-genome studies to catalog events in H5N1 and swine influenza isolates.</p>
</abstract>
</article-meta>
</front>
</pmc>
</record>

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