A benchmark study of k-mer counting methods for high-throughput sequencing
Identifieur interne : 001F94 ( Ncbi/Merge ); précédent : 001F93; suivant : 001F95A benchmark study of k-mer counting methods for high-throughput sequencing
Auteurs : Swati C. Manekar [Inde] ; Shailesh R. Sathe [Inde]Source :
- GigaScience [ 2047-217X ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- genetics : Arabidopsis.
- methods : Computational Biology.
- Animals, Databases, Genetic, Genome, High-Throughput Nucleotide Sequencing, Humans, Sequence Alignment, Sequence Analysis, DNA, Software, Transcriptome.
Abstract
The rapid development of high-throughput sequencing technologies means that hundreds of gigabytes of sequencing data can be produced in a single study. Many bioinformatics tools require counts of substrings of length
Url:
DOI: 10.1093/gigascience/giy125
PubMed: 30346548
PubMed Central: 6280066
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A benchmark study of <italic>k</italic>-mer counting methods for high-throughput sequencing</title><author><name sortKey="Manekar, Swati C" sort="Manekar, Swati C" uniqKey="Manekar S" first="Swati C" last="Manekar">Swati C. Manekar</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30346548</idno><idno type="pmc">6280066</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280066</idno><idno type="RBID">PMC:6280066</idno><idno type="doi">10.1093/gigascience/giy125</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">001341</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001341</idno><idno type="wicri:Area/Pmc/Curation">001341</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">001341</idno><idno type="wicri:Area/Pmc/Checkpoint">000654</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000654</idno><idno type="wicri:source">PubMed</idno><idno type="RBID">pubmed:30346548</idno><idno type="wicri:Area/PubMed/Corpus">000751</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000751</idno><idno type="wicri:Area/PubMed/Curation">000751</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000751</idno><idno type="wicri:Area/PubMed/Checkpoint">000A43</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000A43</idno><idno type="wicri:Area/Ncbi/Merge">001F94</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A benchmark study of <italic>k</italic>-mer counting methods for high-throughput sequencing</title><author><name sortKey="Manekar, Swati C" sort="Manekar, Swati C" uniqKey="Manekar S" first="Swati C" last="Manekar">Swati C. Manekar</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></analytic><series><title level="j">GigaScience</title><idno type="eISSN">2047-217X</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Arabidopsis (genetics)</term><term>Computational Biology (methods)</term><term>Databases, Genetic</term><term>Genome</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Arabidopsis (génétique)</term><term>Bases de données génétiques</term><term>Biologie informatique ()</term><term>Génome</term><term>Humains</term><term>Logiciel</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Arabidopsis</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Arabidopsis</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Databases, Genetic</term><term>Genome</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Génome</term><term>Humains</term><term>Logiciel</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><p>The rapid development of high-throughput sequencing technologies means that hundreds of gigabytes of sequencing data can be produced in a single study. Many bioinformatics tools require counts of substrings of length <italic>k</italic> in DNA/RNA sequencing reads obtained for applications such as genome and transcriptome assembly, error correction, multiple sequence alignment, and repeat detection. Recently, several techniques have been developed to count <italic>k</italic>-mers in large sequencing datasets, with a trade-off between the time and memory required to perform this function. We assessed several <italic>k</italic>-mer counting programs and evaluated their relative performance, primarily on the basis of runtime and memory usage. We also considered additional parameters such as disk usage, accuracy, parallelism, the impact of compressed input, performance in terms of counting large <italic>k</italic> values and the scalability of the application to larger datasets.We make specific recommendations for the setup of a current state-of-the-art program and suggestions for further development.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Reuter, Ja" uniqKey="Reuter J">JA Reuter</name></author><author><name sortKey="Spacek, Dv" uniqKey="Spacek D">DV Spacek</name></author><author><name sortKey="Snyder, Mp" uniqKey="Snyder M">MP Snyder</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Molnar, M" uniqKey="Molnar M">M Molnar</name></author><author><name sortKey="Ilie, L" uniqKey="Ilie L">L Ilie</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Miller, Jr" uniqKey="Miller J">JR 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Birol</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Junior, Lc" uniqKey="Junior L">LC Junior</name></author><author><name sortKey="Brown, Ct" uniqKey="Brown C">CT Brown</name></author></analytic></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><double pmid="30346548"><pmc><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A benchmark study of <italic>k</italic>-mer counting methods for high-throughput sequencing</title><author><name sortKey="Manekar, Swati C" sort="Manekar, Swati C" uniqKey="Manekar S" first="Swati C" last="Manekar">Swati C. Manekar</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30346548</idno><idno type="pmc">6280066</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280066</idno><idno type="RBID">PMC:6280066</idno><idno type="doi">10.1093/gigascience/giy125</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">001341</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001341</idno><idno type="wicri:Area/Pmc/Curation">001341</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">001341</idno><idno type="wicri:Area/Pmc/Checkpoint">000654</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000654</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A benchmark study of <italic>k</italic>-mer counting methods for high-throughput sequencing</title><author><name sortKey="Manekar, Swati C" sort="Manekar, Swati C" uniqKey="Manekar S" first="Swati C" last="Manekar">Swati C. Manekar</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:aff id="aff1">Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></analytic><series><title level="j">GigaScience</title><idno type="eISSN">2047-217X</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><p>The rapid development of high-throughput sequencing technologies means that hundreds of gigabytes of sequencing data can be produced in a single study. Many bioinformatics tools require counts of substrings of length <italic>k</italic> in DNA/RNA sequencing reads obtained for applications such as genome and transcriptome assembly, error correction, multiple sequence alignment, and repeat detection. Recently, several techniques have been developed to count <italic>k</italic>-mers in large sequencing datasets, with a trade-off between the time and memory required to perform this function. We assessed several <italic>k</italic>-mer counting programs and evaluated their relative performance, primarily on the basis of runtime and memory usage. We also considered additional parameters such as disk usage, accuracy, parallelism, the impact of compressed input, performance in terms of counting large <italic>k</italic> values and the scalability of the application to larger datasets.We make specific recommendations for the setup of a current state-of-the-art program and suggestions for further development.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Reuter, Ja" uniqKey="Reuter J">JA Reuter</name></author><author><name sortKey="Spacek, Dv" uniqKey="Spacek D">DV Spacek</name></author><author><name sortKey="Snyder, Mp" uniqKey="Snyder M">MP Snyder</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Molnar, M" uniqKey="Molnar M">M Molnar</name></author><author><name sortKey="Ilie, L" uniqKey="Ilie L">L Ilie</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Miller, Jr" uniqKey="Miller J">JR 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Manekar</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:30346548</idno><idno type="pmid">30346548</idno><idno type="doi">10.1093/gigascience/giy125</idno><idno type="wicri:Area/PubMed/Corpus">000751</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000751</idno><idno type="wicri:Area/PubMed/Curation">000751</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000751</idno><idno type="wicri:Area/PubMed/Checkpoint">000A43</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000A43</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A benchmark study of k-mer counting methods for high-throughput sequencing.</title><author><name sortKey="Manekar, Swati C" sort="Manekar, Swati C" uniqKey="Manekar S" first="Swati C" last="Manekar">Swati C. Manekar</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author><author><name sortKey="Sathe, Shailesh R" sort="Sathe, Shailesh R" uniqKey="Sathe S" first="Shailesh R" last="Sathe">Shailesh R. Sathe</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur 440 010</wicri:regionArea><wicri:noRegion>Nagpur 440 010</wicri:noRegion></affiliation></author></analytic><series><title level="j">GigaScience</title><idno type="eISSN">2047-217X</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Arabidopsis (genetics)</term><term>Computational Biology (methods)</term><term>Databases, Genetic</term><term>Genome</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Arabidopsis (génétique)</term><term>Bases de données génétiques</term><term>Biologie informatique ()</term><term>Génome</term><term>Humains</term><term>Logiciel</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Arabidopsis</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Arabidopsis</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Databases, Genetic</term><term>Genome</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Génome</term><term>Humains</term><term>Logiciel</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The rapid development of high-throughput sequencing technologies means that hundreds of gigabytes of sequencing data can be produced in a single study. Many bioinformatics tools require counts of substrings of length k in DNA/RNA sequencing reads obtained for applications such as genome and transcriptome assembly, error correction, multiple sequence alignment, and repeat detection. Recently, several techniques have been developed to count k-mers in large sequencing datasets, with a trade-off between the time and memory required to perform this function. We assessed several k-mer counting programs and evaluated their relative performance, primarily on the basis of runtime and memory usage. We also considered additional parameters such as disk usage, accuracy, parallelism, the impact of compressed input, performance in terms of counting large k values and the scalability of the application to larger datasets.We make specific recommendations for the setup of a current state-of-the-art program and suggestions for further development.</div></front></TEI></pubmed></double></record>Pour manipuler ce document sous Unix (Dilib)
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