Gerbil: a fast and memory-efficient k-mer counter with GPU-support.
Identifieur interne : 000D36 ( PubMed/Corpus ); précédent : 000D35; suivant : 000D37Gerbil: a fast and memory-efficient k-mer counter with GPU-support.
Auteurs : Marius Erbert ; Steffen Rechner ; Matthias Müller-HannemannSource :
- Algorithms for molecular biology : AMB [ 1748-7188 ] ; 2017.
Abstract
A basic task in bioinformatics is the counting of k-mers in genome sequences. Existing k-mer counting tools are most often optimized for small k < 32 and suffer from excessive memory resource consumption or degrading performance for large k. However, given the technology trend towards long reads of next-generation sequencers, support for large k becomes increasingly important.
DOI: 10.1186/s13015-017-0097-9
PubMed: 28373894
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Gerbil: a fast and memory-efficient <i>k</i>-mer counter with GPU-support.</title><author><name sortKey="Erbert, Marius" sort="Erbert, Marius" uniqKey="Erbert M" first="Marius" last="Erbert">Marius Erbert</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Rechner, Steffen" sort="Rechner, Steffen" uniqKey="Rechner S" first="Steffen" last="Rechner">Steffen Rechner</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Muller Hannemann, Matthias" sort="Muller Hannemann, Matthias" uniqKey="Muller Hannemann M" first="Matthias" last="Müller-Hannemann">Matthias Müller-Hannemann</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28373894</idno><idno type="pmid">28373894</idno><idno type="doi">10.1186/s13015-017-0097-9</idno><idno type="wicri:Area/PubMed/Corpus">000D36</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000D36</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Gerbil: a fast and memory-efficient <i>k</i>-mer counter with GPU-support.</title><author><name sortKey="Erbert, Marius" sort="Erbert, Marius" uniqKey="Erbert M" first="Marius" last="Erbert">Marius Erbert</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Rechner, Steffen" sort="Rechner, Steffen" uniqKey="Rechner S" first="Steffen" last="Rechner">Steffen Rechner</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Muller Hannemann, Matthias" sort="Muller Hannemann, Matthias" uniqKey="Muller Hannemann M" first="Matthias" last="Müller-Hannemann">Matthias Müller-Hannemann</name><affiliation><nlm:affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Algorithms for molecular biology : AMB</title><idno type="ISSN">1748-7188</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A basic task in bioinformatics is the counting of <i>k</i>-mers in genome sequences. Existing <i>k</i>-mer counting tools are most often optimized for small <i>k</i> < 32 and suffer from excessive memory resource consumption or degrading performance for large <i>k</i>. However, given the technology trend towards long reads of next-generation sequencers, support for large <i>k</i> becomes increasingly important.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">28373894</PMID><DateRevised><Year>2019</Year><Month>11</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1748-7188</ISSN><JournalIssue CitedMedium="Print"><Volume>12</Volume><PubDate><Year>2017</Year></PubDate></JournalIssue><Title>Algorithms for molecular biology : AMB</Title><ISOAbbreviation>Algorithms Mol Biol</ISOAbbreviation></Journal><ArticleTitle>Gerbil: a fast and memory-efficient <i>k</i>-mer counter with GPU-support.</ArticleTitle><Pagination><MedlinePgn>9</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s13015-017-0097-9</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">A basic task in bioinformatics is the counting of <i>k</i>-mers in genome sequences. Existing <i>k</i>-mer counting tools are most often optimized for small <i>k</i> < 32 and suffer from excessive memory resource consumption or degrading performance for large <i>k</i>. However, given the technology trend towards long reads of next-generation sequencers, support for large <i>k</i> becomes increasingly important.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">We present the open source <i>k</i>-mer counting software <i>Gerbil</i> that has been designed for the efficient counting of <i>k</i>-mers for <i>k</i> ≥ 32. Our software is the result of an intensive process of algorithm engineering. It implements a two-step approach. In the first step, genome reads are loaded from disk and redistributed to temporary files. In a second step, the <i>k</i>-mers of each temporary file are counted via a hash table approach. In addition to its basic functionality, <i>Gerbil</i> can optionally use GPUs to accelerate the counting step. In a set of experiments with real-world genome data sets, we show that <i>Gerbil</i> is able to efficiently support both small and large <i>k</i>.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">While <i>Gerbil</i>'s performance is comparable to existing state-of-the-art open source <i>k</i>-mer counting tools for small <i>k</i> < 32, it vastly outperforms its competitors for large <i>k</i>, thereby enabling new applications which require large values of <i>k</i>.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Erbert</LastName><ForeName>Marius</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</Affiliation><Identifier Source="GRID">grid.9018.0</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rechner</LastName><ForeName>Steffen</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</Affiliation><Identifier Source="GRID">grid.9018.0</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Müller-Hannemann</LastName><ForeName>Matthias</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.</Affiliation><Identifier Source="GRID">grid.9018.0</Identifier></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>03</Month><Day>31</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Algorithms Mol Biol</MedlineTA><NlmUniqueID>101265088</NlmUniqueID><ISSNLinking>1748-7188</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Algorithm engineering</Keyword><Keyword MajorTopicYN="N">GPU computing</Keyword><Keyword MajorTopicYN="N">Genome sequences</Keyword><Keyword MajorTopicYN="N">de novo assembly</Keyword><Keyword MajorTopicYN="N">k-mer counting</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>12</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>02</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>4</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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