MetaCache: context-aware classification of metagenomic reads using minhashing.
Identifieur interne : 000C26 ( PubMed/Checkpoint ); précédent : 000C25; suivant : 000C27MetaCache: context-aware classification of metagenomic reads using minhashing.
Auteurs : André Müller ; Christian Hundt ; Andreas Hildebrandt ; Thomas Hankeln [Allemagne] ; Bertil SchmidtSource :
- Bioinformatics (Oxford, England) [ 1367-4811 ] ; 2017.
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Abstract
Metagenomic shotgun sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification, i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy.
DOI: 10.1093/bioinformatics/btx520
PubMed: 28961782
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Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author><author><name sortKey="Hankeln, Thomas" sort="Hankeln, Thomas" uniqKey="Hankeln T" first="Thomas" last="Hankeln">Thomas Hankeln</name><affiliation wicri:level="3"><nlm:affiliation>Molecular Genetics and Genome Analysis Group, Department of Biology, Department of Biology, Johannes Gutenberg University, 55128 Mainz, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Molecular Genetics and Genome Analysis Group, Department of Biology, Department of Biology, Johannes Gutenberg University, 55128 Mainz</wicri:regionArea><placeName><region type="land" nuts="2">Rhénanie-Palatinat</region><settlement type="city">Mayence</settlement></placeName></affiliation></author><author><name sortKey="Schmidt, Bertil" sort="Schmidt, Bertil" uniqKey="Schmidt B" first="Bertil" last="Schmidt">Bertil Schmidt</name><affiliation><nlm:affiliation>Department of Computer Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28961782</idno><idno type="pmid">28961782</idno><idno type="doi">10.1093/bioinformatics/btx520</idno><idno type="wicri:Area/PubMed/Corpus">000B35</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000B35</idno><idno type="wicri:Area/PubMed/Curation">000B35</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000B35</idno><idno type="wicri:Area/PubMed/Checkpoint">000C26</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000C26</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">MetaCache: context-aware classification of metagenomic reads using minhashing.</title><author><name sortKey="Muller, Andre" sort="Muller, Andre" uniqKey="Muller A" first="André" last="Müller">André Müller</name><affiliation><nlm:affiliation>Department of Computer Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author><author><name sortKey="Hundt, Christian" sort="Hundt, Christian" uniqKey="Hundt C" first="Christian" last="Hundt">Christian Hundt</name><affiliation><nlm:affiliation>Department of Computer Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author><author><name sortKey="Hildebrandt, Andreas" sort="Hildebrandt, Andreas" uniqKey="Hildebrandt A" first="Andreas" last="Hildebrandt">Andreas Hildebrandt</name><affiliation><nlm:affiliation>Department of Computer Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author><author><name sortKey="Hankeln, Thomas" sort="Hankeln, Thomas" uniqKey="Hankeln T" first="Thomas" last="Hankeln">Thomas Hankeln</name><affiliation wicri:level="3"><nlm:affiliation>Molecular Genetics and Genome Analysis Group, Department of Biology, Department of Biology, Johannes Gutenberg University, 55128 Mainz, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Molecular Genetics and Genome Analysis Group, Department of Biology, Department of Biology, Johannes Gutenberg University, 55128 Mainz</wicri:regionArea><placeName><region type="land" nuts="2">Rhénanie-Palatinat</region><settlement type="city">Mayence</settlement></placeName></affiliation></author><author><name sortKey="Schmidt, Bertil" sort="Schmidt, Bertil" uniqKey="Schmidt B" first="Bertil" last="Schmidt">Bertil Schmidt</name><affiliation><nlm:affiliation>Department of Computer Science.</nlm:affiliation><wicri:noCountry code="no comma">Department of Computer Science.</wicri:noCountry></affiliation></author></analytic><series><title level="j">Bioinformatics (Oxford, England)</title><idno type="eISSN">1367-4811</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Metagenomics (methods)</term><term>Sequence Analysis, DNA</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Analyse de séquence d'ADN</term><term>Humains</term><term>Logiciel</term><term>Métagénomique ()</term><term>Séquençage nucléotidique à haut débit</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Metagenomics</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Sequence Analysis, DNA</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Analyse de séquence d'ADN</term><term>Humains</term><term>Logiciel</term><term>Métagénomique</term><term>Séquençage nucléotidique à haut débit</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Metagenomic shotgun sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification, i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">28961782</PMID><DateCompleted><Year>2018</Year><Month>08</Month><Day>02</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1367-4811</ISSN><JournalIssue CitedMedium="Internet"><Volume>33</Volume><Issue>23</Issue><PubDate><Year>2017</Year><Month>Dec</Month><Day>01</Day></PubDate></JournalIssue><Title>Bioinformatics (Oxford, England)</Title><ISOAbbreviation>Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>MetaCache: context-aware classification of metagenomic reads using minhashing.</ArticleTitle><Pagination><MedlinePgn>3740-3748</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/bioinformatics/btx520</ELocationID><Abstract><AbstractText Label="Motivation" NlmCategory="UNASSIGNED">Metagenomic shotgun sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification, i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">We introduce MetaCache-a novel software for read classification using the big data technique minhashing. Our approach performs context-aware classification of reads by computing representative subsamples of k-mers within both, probed reads and locally constrained regions of the reference genomes. As a result, MetaCache consumes significantly less memory compared to the state-of-the-art read classifiers Kraken and CLARK while achieving highly competitive sensitivity and precision at comparable speed. For example, using NCBI RefSeq draft and completed genomes with a total length of around 140 billion bases as reference, MetaCache's database consumes only 62 GB of memory while both Kraken and CLARK fail to construct their respective databases on a workstation with 512 GB RAM. Our experimental results further show that classification accuracy continuously improves when increasing the amount of utilized reference genome data.</AbstractText><AbstractText Label="Availability and implementation" NlmCategory="UNASSIGNED">MetaCache is open source software written in C ++ and can be downloaded at http://github.com/muellan/metacache.</AbstractText><AbstractText Label="Contact" NlmCategory="UNASSIGNED">bertil.schmidt@uni-mainz.de.</AbstractText><AbstractText Label="Supplementary information" NlmCategory="UNASSIGNED">Supplementary data are available at Bioinformatics online.</AbstractText><CopyrightInformation>© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Müller</LastName><ForeName>André</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Computer Science.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hundt</LastName><ForeName>Christian</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Computer Science.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hildebrandt</LastName><ForeName>Andreas</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Computer Science.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hankeln</LastName><ForeName>Thomas</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Molecular Genetics and Genome Analysis Group, Department of Biology, Department of Biology, Johannes Gutenberg University, 55128 Mainz, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schmidt</LastName><ForeName>Bertil</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Computer Science.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Bioinformatics</MedlineTA><NlmUniqueID>9808944</NlmUniqueID><ISSNLinking>1367-4803</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="N">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D059014" MajorTopicYN="N">High-Throughput Nucleotide Sequencing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D056186" MajorTopicYN="N">Metagenomics</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012984" MajorTopicYN="Y">Software</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>02</Month><Day>15</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>08</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>9</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>8</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>9</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">28961782</ArticleId><ArticleId IdType="pii">4083578</ArticleId><ArticleId IdType="doi">10.1093/bioinformatics/btx520</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Allemagne</li></country><region><li>Rhénanie-Palatinat</li></region><settlement><li>Mayence</li></settlement></list><tree><noCountry><name sortKey="Hildebrandt, Andreas" sort="Hildebrandt, Andreas" uniqKey="Hildebrandt A" first="Andreas" last="Hildebrandt">Andreas Hildebrandt</name><name sortKey="Hundt, Christian" sort="Hundt, Christian" uniqKey="Hundt C" first="Christian" last="Hundt">Christian Hundt</name><name sortKey="Muller, Andre" sort="Muller, Andre" uniqKey="Muller A" first="André" last="Müller">André Müller</name><name sortKey="Schmidt, Bertil" sort="Schmidt, Bertil" uniqKey="Schmidt B" first="Bertil" last="Schmidt">Bertil Schmidt</name></noCountry><country name="Allemagne"><region name="Rhénanie-Palatinat"><name sortKey="Hankeln, Thomas" sort="Hankeln, Thomas" uniqKey="Hankeln T" first="Thomas" last="Hankeln">Thomas Hankeln</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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