A primer on metagenomics.
Identifieur interne : 000064 ( PubMed/Corpus ); précédent : 000063; suivant : 000065A primer on metagenomics.
Auteurs : John C. Wooley ; Adam Godzik ; Iddo FriedbergSource :
- PLoS computational biology [ 1553-7358 ] ; 2010.
English descriptors
- KwdEn :
- MESH :
Abstract
Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics.
DOI: 10.1371/journal.pcbi.1000667
PubMed: 20195499
Links to Exploration step
pubmed:20195499Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A primer on metagenomics.</title><author><name sortKey="Wooley, John C" sort="Wooley, John C" uniqKey="Wooley J" first="John C" last="Wooley">John C. Wooley</name><affiliation><nlm:affiliation>Community Cyberinfrastructure for Marine Microbial Ecology Research and Analysis, California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Godzik, Adam" sort="Godzik, Adam" uniqKey="Godzik A" first="Adam" last="Godzik">Adam Godzik</name></author><author><name sortKey="Friedberg, Iddo" sort="Friedberg, Iddo" uniqKey="Friedberg I" first="Iddo" last="Friedberg">Iddo Friedberg</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2010">2010</date><idno type="doi">10.1371/journal.pcbi.1000667</idno><idno type="RBID">pubmed:20195499</idno><idno type="pmid">20195499</idno><idno type="wicri:Area/PubMed/Corpus">000064</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A primer on metagenomics.</title><author><name sortKey="Wooley, John C" sort="Wooley, John C" uniqKey="Wooley J" first="John C" last="Wooley">John C. Wooley</name><affiliation><nlm:affiliation>Community Cyberinfrastructure for Marine Microbial Ecology Research and Analysis, California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Godzik, Adam" sort="Godzik, Adam" uniqKey="Godzik A" first="Adam" last="Godzik">Adam Godzik</name></author><author><name sortKey="Friedberg, Iddo" sort="Friedberg, Iddo" uniqKey="Friedberg I" first="Iddo" last="Friedberg">Iddo Friedberg</name></author></analytic><series><title level="j">PLoS computational biology</title><idno type="eISSN">1553-7358</idno><imprint><date when="2010" type="published">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computational Biology</term><term>Metagenomics</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computational Biology</term><term>Metagenomics</term><term>Sequence Analysis, DNA</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">20195499</PMID><DateCreated><Year>2010</Year><Month>03</Month><Day>02</Day></DateCreated><DateCompleted><Year>2010</Year><Month>05</Month><Day>10</Day></DateCompleted><DateRevised><Year>2014</Year><Month>12</Month><Day>04</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1553-7358</ISSN><JournalIssue CitedMedium="Internet"><Volume>6</Volume><Issue>2</Issue><PubDate><Year>2010</Year><Month>Feb</Month></PubDate></JournalIssue><Title>PLoS computational biology</Title><ISOAbbreviation>PLoS Comput. Biol.</ISOAbbreviation></Journal><ArticleTitle>A primer on metagenomics.</ArticleTitle><Pagination><MedlinePgn>e1000667</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pcbi.1000667</ELocationID><Abstract><AbstractText>Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wooley</LastName><ForeName>John C</ForeName><Initials>JC</Initials><AffiliationInfo><Affiliation>Community Cyberinfrastructure for Marine Microbial Ecology Research and Analysis, California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Godzik</LastName><ForeName>Adam</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Friedberg</LastName><ForeName>Iddo</ForeName><Initials>I</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2010</Year><Month>02</Month><Day>26</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS Comput Biol</MedlineTA><NlmUniqueID>101238922</NlmUniqueID><ISSNLinking>1553-734X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Genome Res. 2008 Jun;18(6):839-46</RefSource><PMID Version="1">18519653</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>BMC Bioinformatics. 2008;9:217</RefSource><PMID Version="1">18442389</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Nat Methods. 2009 Sep;6(9):673-6</RefSource><PMID Version="1">19648916</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Nature. 2009 Sep 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DNA</DescriptorName></MeshHeading></MeshHeadingList><NumberOfReferences>135</NumberOfReferences><OtherID Source="NLM">PMC2829047</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="epublish"><Year>2010</Year><Month>2</Month><Day>26</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2010</Year><Month>3</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2010</Year><Month>3</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2010</Year><Month>5</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1371/journal.pcbi.1000667</ArticleId><ArticleId IdType="pubmed">20195499</ArticleId><ArticleId IdType="pmc">PMC2829047</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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