Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.
Identifieur interne : 000337 ( PubMed/Corpus ); précédent : 000336; suivant : 000338Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.
Auteurs : Javier Tamames ; Marta Cobo-Sim N ; Fernando Puente-SánchezSource :
- BMC genomics [ 1471-2164 ] ; 2019.
Abstract
Metagenomes can be analysed using different approaches and tools. One of the most important distinctions is the way to perform taxonomic and functional assignment, choosing between the use of assembly algorithms or the direct analysis of raw sequence reads instead by homology searching, k-mer analysys, or detection of marker genes. Many instances of each approach can be found in the literature, but to the best of our knowledge no evaluation of their different performances has been carried on, and we question if their results are comparable.
DOI: 10.1186/s12864-019-6289-6
PubMed: 31823721
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.</title><author><name sortKey="Tamames, Javier" sort="Tamames, Javier" uniqKey="Tamames J" first="Javier" last="Tamames">Javier Tamames</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain. jtamames@cnb.csic.es.</nlm:affiliation></affiliation></author><author><name sortKey="Cobo Sim N, Marta" sort="Cobo Sim N, Marta" uniqKey="Cobo Sim N M" first="Marta" last="Cobo-Sim N">Marta Cobo-Sim N</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</nlm:affiliation></affiliation></author><author><name sortKey="Puente Sanchez, Fernando" sort="Puente Sanchez, Fernando" uniqKey="Puente Sanchez F" first="Fernando" last="Puente-Sánchez">Fernando Puente-Sánchez</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2019">2019</date><idno type="RBID">pubmed:31823721</idno><idno type="pmid">31823721</idno><idno type="doi">10.1186/s12864-019-6289-6</idno><idno type="wicri:Area/PubMed/Corpus">000337</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000337</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.</title><author><name sortKey="Tamames, Javier" sort="Tamames, Javier" uniqKey="Tamames J" first="Javier" last="Tamames">Javier Tamames</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain. jtamames@cnb.csic.es.</nlm:affiliation></affiliation></author><author><name sortKey="Cobo Sim N, Marta" sort="Cobo Sim N, Marta" uniqKey="Cobo Sim N M" first="Marta" last="Cobo-Sim N">Marta Cobo-Sim N</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</nlm:affiliation></affiliation></author><author><name sortKey="Puente Sanchez, Fernando" sort="Puente Sanchez, Fernando" uniqKey="Puente Sanchez F" first="Fernando" last="Puente-Sánchez">Fernando Puente-Sánchez</name><affiliation><nlm:affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</nlm:affiliation></affiliation></author></analytic><series><title level="j">BMC genomics</title><idno type="eISSN">1471-2164</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Metagenomes can be analysed using different approaches and tools. One of the most important distinctions is the way to perform taxonomic and functional assignment, choosing between the use of assembly algorithms or the direct analysis of raw sequence reads instead by homology searching, k-mer analysys, or detection of marker genes. Many instances of each approach can be found in the literature, but to the best of our knowledge no evaluation of their different performances has been carried on, and we question if their results are comparable.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">31823721</PMID><DateRevised><Year>2020</Year><Month>02</Month><Day>05</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2164</ISSN><JournalIssue CitedMedium="Internet"><Volume>20</Volume><Issue>1</Issue><PubDate><Year>2019</Year><Month>Dec</Month><Day>10</Day></PubDate></JournalIssue><Title>BMC genomics</Title><ISOAbbreviation>BMC Genomics</ISOAbbreviation></Journal><ArticleTitle>Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.</ArticleTitle><Pagination><MedlinePgn>960</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12864-019-6289-6</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Metagenomes can be analysed using different approaches and tools. One of the most important distinctions is the way to perform taxonomic and functional assignment, choosing between the use of assembly algorithms or the direct analysis of raw sequence reads instead by homology searching, k-mer analysys, or detection of marker genes. Many instances of each approach can be found in the literature, but to the best of our knowledge no evaluation of their different performances has been carried on, and we question if their results are comparable.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">We have analysed several real and mock metagenomes using different methodologies and tools, and compared the resulting taxonomic and functional profiles. Our results show that database completeness (the representation of diverse organisms and taxa in it) is the main factor determining the performance of the methods relying on direct read assignment either by homology, k-mer composition or similarity to marker genes, while methods relying on assembly and assignment of predicted genes are most influenced by metagenomic size, that in turn determines the completeness of the assembly (the percentage of read that were assembled).</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Although differences exist, taxonomic profiles are rather similar between raw read assignment and assembly assignment methods, while they are more divergent for methods based on k-mers and marker genes. Regarding functional annotation, analysis of raw reads retrieves more functions, but it also makes a substantial number of over-predictions. Assembly methods are more advantageous as the size of the metagenome grows bigger.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Tamames</LastName><ForeName>Javier</ForeName><Initials>J</Initials><Identifier Source="ORCID">http://orcid.org/0000-0003-4547-8932</Identifier><AffiliationInfo><Affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain. jtamames@cnb.csic.es.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cobo-Simón</LastName><ForeName>Marta</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Puente-Sánchez</LastName><ForeName>Fernando</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Systems Biology Department, Centro Nacional de Biotecnología, CSIC, C/Darwin 3, 28049, Madrid, Spain.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>CTM2013-48292-C3-2-R</GrantID><Agency>Ministerio de Economía, Industria y Competitividad, Gobierno de España</Agency><Country></Country></Grant><Grant><GrantID>CTM2016-80095-C2-1-R</GrantID><Agency>Ministerio de Economía, Industria y Competitividad, Gobierno de España</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>12</Month><Day>10</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Genomics</MedlineTA><NlmUniqueID>100965258</NlmUniqueID><ISSNLinking>1471-2164</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Assembly</Keyword><Keyword MajorTopicYN="N">Functional 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