Efficient computation of spaced seed hashing with block indexing
Identifieur interne : 000593 ( Pmc/Checkpoint ); précédent : 000592; suivant : 000594Efficient computation of spaced seed hashing with block indexing
Auteurs : Samuele Girotto ; Matteo Comin ; Cinzia PizziSource :
- BMC Bioinformatics [ 1471-2105 ] ; 2018.
Abstract
Spaced-seeds, i.e. patterns in which some fixed positions are allowed to be wild-cards, play a crucial role in several bioinformatics applications involving substrings counting and indexing, by often providing better sensitivity with respect to
In this work we propose a novel algorithm, Fast Indexing for Spaced seed Hashing (FISH), based on the indexing of small blocks that can be combined to obtain the hashing of spaced-seeds of any length. The method exploits the fast computation of the hashing of runs of consecutive 1 in the spaced seeds, that basically correspond to
We run several experiments, on NGS data from simulated and synthetic metagenomic experiments, to assess the time required for the computation of the hashing for each position in each read with respect to several spaced seeds. In our experiments, FISH can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.9x to 6.03x, depending on the structure of the spaced seeds.
The online version of this article (10.1186/s12859-018-2415-8) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12859-018-2415-8
PubMed: 30497364
PubMed Central: 6266934
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Efficient computation of spaced seed hashing with block indexing</title><author><name sortKey="Girotto, Samuele" sort="Girotto, Samuele" uniqKey="Girotto S" first="Samuele" last="Girotto">Samuele Girotto</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Comin, Matteo" sort="Comin, Matteo" uniqKey="Comin M" first="Matteo" last="Comin">Matteo Comin</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Pizzi, Cinzia" sort="Pizzi, Cinzia" uniqKey="Pizzi C" first="Cinzia" last="Pizzi">Cinzia Pizzi</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30497364</idno><idno type="pmc">6266934</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266934</idno><idno type="RBID">PMC:6266934</idno><idno type="doi">10.1186/s12859-018-2415-8</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">000277</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000277</idno><idno type="wicri:Area/Pmc/Curation">000277</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000277</idno><idno type="wicri:Area/Pmc/Checkpoint">000593</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000593</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Efficient computation of spaced seed hashing with block indexing</title><author><name sortKey="Girotto, Samuele" sort="Girotto, Samuele" uniqKey="Girotto S" first="Samuele" last="Girotto">Samuele Girotto</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Comin, Matteo" sort="Comin, Matteo" uniqKey="Comin M" first="Matteo" last="Comin">Matteo Comin</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Pizzi, Cinzia" sort="Pizzi, Cinzia" uniqKey="Pizzi C" first="Cinzia" last="Pizzi">Cinzia Pizzi</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Spaced-seeds, i.e. patterns in which some fixed positions are allowed to be wild-cards, play a crucial role in several bioinformatics applications involving substrings counting and indexing, by often providing better sensitivity with respect to <italic>k</italic>-mers based approaches. K-mers based approaches are usually fast, being based on efficient hashing and indexing that exploits the large overlap between consecutive <italic>k</italic>-mers. Spaced-seeds hashing is not as straightforward, and it is usually computed from scratch for each position in the input sequence. Recently, the FSH (Fast Spaced seed Hashing) approach was proposed to improve the time required for computation of the spaced seed hashing of DNA sequences with a speed-up of about 1.5 with respect to standard hashing computation.</p></sec><sec><title>Results</title><p>In this work we propose a novel algorithm, Fast Indexing for Spaced seed Hashing (FISH), based on the indexing of small blocks that can be combined to obtain the hashing of spaced-seeds of any length. The method exploits the fast computation of the hashing of runs of consecutive 1 in the spaced seeds, that basically correspond to <italic>k</italic>-mer of the length of the run.</p></sec><sec><title>Conclusions</title><p>We run several experiments, on NGS data from simulated and synthetic metagenomic experiments, to assess the time required for the computation of the hashing for each position in each read with respect to several spaced seeds. In our experiments, FISH can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.9x to 6.03x, depending on the structure of the spaced seeds.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (10.1186/s12859-018-2415-8) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Altschul, Sf" uniqKey="Altschul S">SF Altschul</name></author><author><name sortKey="Gish, W" uniqKey="Gish W">W Gish</name></author><author><name sortKey="Miller, W" uniqKey="Miller W">W Miller</name></author><author><name sortKey="Myers, Ew" uniqKey="Myers E">EW Myers</name></author><author><name sortKey="Lipman, Dj" uniqKey="Lipman D">DJ Lipman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zielezinski, A" uniqKey="Zielezinski A">A 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id><journal-id journal-id-type="iso-abbrev">BMC Bioinformatics</journal-id><journal-title-group><journal-title>BMC Bioinformatics</journal-title></journal-title-group><issn pub-type="epub">1471-2105</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30497364</article-id><article-id pub-id-type="pmc">6266934</article-id><article-id pub-id-type="publisher-id">2415</article-id><article-id pub-id-type="doi">10.1186/s12859-018-2415-8</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research</subject></subj-group></article-categories><title-group><article-title>Efficient computation of spaced seed hashing with block indexing</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Girotto</surname><given-names>Samuele</given-names></name><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Comin</surname><given-names>Matteo</given-names></name><address><email>comin@dei.unipd.it</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Pizzi</surname><given-names>Cinzia</given-names></name><address><email>cinzia.pizzi@dei.unipd.it</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><aff id="Aff1"><institution-wrap><institution-id institution-id-type="ISNI">0000 0004 1757 3470</institution-id><institution-id institution-id-type="GRID">grid.5608.b</institution-id><institution>Department of Information Engineering, University of Padova,</institution></institution-wrap>via Gradenigo 6/A, Padova, Italy</aff></contrib-group><pub-date pub-type="epub"><day>30</day><month>11</month><year>2018</year></pub-date><pub-date pub-type="pmc-release"><day>30</day><month>11</month><year>2018</year></pub-date><pub-date pub-type="collection"><year>2018</year></pub-date><volume>19</volume><issue>Suppl 15</issue><issue-sponsor>Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.</issue-sponsor><elocation-id>441</elocation-id><permissions><copyright-statement>© The Author(s) 2018</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold> This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p>Spaced-seeds, i.e. patterns in which some fixed positions are allowed to be wild-cards, play a crucial role in several bioinformatics applications involving substrings counting and indexing, by often providing better sensitivity with respect to <italic>k</italic>-mers based approaches. K-mers based approaches are usually fast, being based on efficient hashing and indexing that exploits the large overlap between consecutive <italic>k</italic>-mers. Spaced-seeds hashing is not as straightforward, and it is usually computed from scratch for each position in the input sequence. Recently, the FSH (Fast Spaced seed Hashing) approach was proposed to improve the time required for computation of the spaced seed hashing of DNA sequences with a speed-up of about 1.5 with respect to standard hashing computation.</p></sec><sec><title>Results</title><p>In this work we propose a novel algorithm, Fast Indexing for Spaced seed Hashing (FISH), based on the indexing of small blocks that can be combined to obtain the hashing of spaced-seeds of any length. The method exploits the fast computation of the hashing of runs of consecutive 1 in the spaced seeds, that basically correspond to <italic>k</italic>-mer of the length of the run.</p></sec><sec><title>Conclusions</title><p>We run several experiments, on NGS data from simulated and synthetic metagenomic experiments, to assess the time required for the computation of the hashing for each position in each read with respect to several spaced seeds. In our experiments, FISH can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.9x to 6.03x, depending on the structure of the spaced seeds.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (10.1186/s12859-018-2415-8) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Spaced seeds</kwd><kwd>k-mers</kwd><kwd>Efficient computation of hashing</kwd></kwd-group><conference xlink:href="https://www.bbcc-meetings.it/"><conf-name>BBCC Conference 2017</conf-name><conf-acronym>BBCC 2017</conf-acronym><conf-loc>Naples, Italy</conf-loc><conf-date>18 - 20 December 2017</conf-date></conference><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2018</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Comin, Matteo" sort="Comin, Matteo" uniqKey="Comin M" first="Matteo" last="Comin">Matteo Comin</name><name sortKey="Girotto, Samuele" sort="Girotto, Samuele" uniqKey="Girotto S" first="Samuele" last="Girotto">Samuele Girotto</name><name sortKey="Pizzi, Cinzia" sort="Pizzi, Cinzia" uniqKey="Pizzi C" first="Cinzia" last="Pizzi">Cinzia Pizzi</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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