KMC 2: fast and resource-frugal k-mer counting.
Identifieur interne : 001022 ( Ncbi/Merge ); précédent : 001021; suivant : 001023KMC 2: fast and resource-frugal k-mer counting.
Auteurs : Sebastian Deorowicz [Pologne] ; Marek Kokot [Pologne] ; Szymon Grabowski [Pologne] ; Agnieszka Debudaj-Grabysz [Pologne]Source :
- Bioinformatics (Oxford, England) [ 1367-4811 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- methods : Computational Biology, Sequence Alignment, Sequence Analysis, DNA.
- Algorithms, Animals, Humans, Software.
Abstract
Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory.
DOI: 10.1093/bioinformatics/btv022
PubMed: 25609798
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Politechniki 11, 90-924 Łódź, Poland.</nlm:affiliation><country xml:lang="fr">Pologne</country><wicri:regionArea>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź</wicri:regionArea><wicri:noRegion>90-924 Łódź</wicri:noRegion></affiliation></author><author><name sortKey="Kokot, Marek" sort="Kokot, Marek" uniqKey="Kokot M" first="Marek" last="Kokot">Marek Kokot</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.</nlm:affiliation><country xml:lang="fr">Pologne</country><wicri:regionArea>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź</wicri:regionArea><wicri:noRegion>90-924 Łódź</wicri:noRegion></affiliation></author><author><name sortKey="Grabowski, Szymon" sort="Grabowski, Szymon" uniqKey="Grabowski S" first="Szymon" last="Grabowski">Szymon Grabowski</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. 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Politechniki 11, 90-924 Łódź, Poland.</nlm:affiliation><country xml:lang="fr">Pologne</country><wicri:regionArea>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź</wicri:regionArea><wicri:noRegion>90-924 Łódź</wicri:noRegion></affiliation></author></analytic><series><title level="j">Bioinformatics (Oxford, England)</title><idno type="eISSN">1367-4811</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Computational Biology (methods)</term><term>Humans</term><term>Sequence Alignment (methods)</term><term>Sequence Analysis, DNA (methods)</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Alignement de séquences ()</term><term>Analyse de séquence d'ADN ()</term><term>Animaux</term><term>Biologie informatique ()</term><term>Humains</term><term>Logiciel</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Humans</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Biologie informatique</term><term>Humains</term><term>Logiciel</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">25609798</PMID><DateCompleted><Year>2015</Year><Month>10</Month><Day>13</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1367-4811</ISSN><JournalIssue CitedMedium="Internet"><Volume>31</Volume><Issue>10</Issue><PubDate><Year>2015</Year><Month>May</Month><Day>15</Day></PubDate></JournalIssue><Title>Bioinformatics (Oxford, England)</Title><ISOAbbreviation>Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>KMC 2: fast and resource-frugal k-mer counting.</ArticleTitle><Pagination><MedlinePgn>1569-76</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/bioinformatics/btv022</ELocationID><Abstract><AbstractText Label="MOTIVATION" NlmCategory="BACKGROUND">Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">We present a novel method for k-mer counting, on large datasets about twice faster than the strongest competitors (Jellyfish 2, KMC 1), using about 12 GB (or less) of RAM. Our disk-based method bears some resemblance to MSPKmerCounter, yet replacing the original minimizers with signatures (a carefully selected subset of all minimizers) and using (k, x)-mers allows to significantly reduce the I/O and a highly parallel overall architecture allows to achieve unprecedented processing speeds. For example, KMC 2 counts the 28-mers of a human reads collection with 44-fold coverage (106 GB of compressed size) in about 20 min, on a 6-core Intel i7 PC with an solid-state disk.</AbstractText><CopyrightInformation>© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Deorowicz</LastName><ForeName>Sebastian</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kokot</LastName><ForeName>Marek</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Grabowski</LastName><ForeName>Szymon</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Debudaj-Grabysz</LastName><ForeName>Agnieszka</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>01</Month><Day>20</Day></ArticleDate></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="Y">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019295" MajorTopicYN="N">Computational Biology</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016415" MajorTopicYN="N">Sequence Alignment</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012984" MajorTopicYN="Y">Software</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>07</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>01</Month><Day>12</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>1</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>1</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>10</Month><Day>16</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25609798</ArticleId><ArticleId IdType="pii">btv022</ArticleId><ArticleId IdType="doi">10.1093/bioinformatics/btv022</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Pologne</li></country></list><tree><country name="Pologne"><noRegion><name sortKey="Deorowicz, Sebastian" sort="Deorowicz, Sebastian" uniqKey="Deorowicz S" first="Sebastian" last="Deorowicz">Sebastian Deorowicz</name></noRegion><name sortKey="Debudaj Grabysz, Agnieszka" sort="Debudaj Grabysz, Agnieszka" uniqKey="Debudaj Grabysz A" first="Agnieszka" last="Debudaj-Grabysz">Agnieszka Debudaj-Grabysz</name><name sortKey="Grabowski, Szymon" sort="Grabowski, Szymon" uniqKey="Grabowski S" first="Szymon" last="Grabowski">Szymon Grabowski</name><name sortKey="Kokot, Marek" sort="Kokot, Marek" uniqKey="Kokot M" first="Marek" last="Kokot">Marek Kokot</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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