Kevlar: A Mapping-Free Framework for Accurate Discovery of De Novo Variants
Identifieur interne : 001231 ( Pmc/Curation ); précédent : 001230; suivant : 001232Kevlar: A Mapping-Free Framework for Accurate Discovery of De Novo Variants
Auteurs : Daniel S. Standage [États-Unis] ; C. Titus Brown [États-Unis] ; Fereydoun Hormozdiari [États-Unis]Source :
- iScience [ 2589-0042 ] ; 2019.
Abstract
Url:
DOI: 10.1016/j.isci.2019.07.032
PubMed: 31377530
PubMed Central: 6682328
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Kevlar: A Mapping-Free Framework for Accurate Discovery of <italic>De Novo</italic> Variants</title><author><name sortKey="Standage, Daniel S" sort="Standage, Daniel S" uniqKey="Standage D" first="Daniel S." last="Standage">Daniel S. Standage</name><affiliation wicri:level="1"><nlm:aff id="aff1">Population Health and Reproduction, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Population Health and Reproduction, University of California, Davis</wicri:regionArea></affiliation></author><author><name sortKey="Brown, C Titus" sort="Brown, C Titus" uniqKey="Brown C" first="C. Titus" last="Brown">C. Titus Brown</name><affiliation wicri:level="1"><nlm:aff id="aff1">Population Health and Reproduction, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Population Health and Reproduction, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff2">Genome Center, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Genome Center, University of California, Davis</wicri:regionArea></affiliation></author><author><name sortKey="Hormozdiari, Fereydoun" sort="Hormozdiari, Fereydoun" uniqKey="Hormozdiari F" first="Fereydoun" last="Hormozdiari">Fereydoun Hormozdiari</name><affiliation wicri:level="1"><nlm:aff id="aff2">Genome Center, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Genome Center, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3">MIND Institute, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>MIND Institute, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4">Biochemistry and Molecular Medicine, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Biochemistry and Molecular Medicine, University of California, Davis, 1 Shields Avenue, Davis, CA 95616</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">31377530</idno><idno type="pmc">6682328</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682328</idno><idno type="RBID">PMC:6682328</idno><idno type="doi">10.1016/j.isci.2019.07.032</idno><date when="2019">2019</date><idno type="wicri:Area/Pmc/Corpus">001231</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001231</idno><idno type="wicri:Area/Pmc/Curation">001231</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">001231</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Kevlar: A Mapping-Free Framework for Accurate Discovery of <italic>De Novo</italic> Variants</title><author><name sortKey="Standage, Daniel S" sort="Standage, Daniel S" uniqKey="Standage D" first="Daniel S." last="Standage">Daniel S. Standage</name><affiliation wicri:level="1"><nlm:aff id="aff1">Population Health and Reproduction, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Population Health and Reproduction, University of California, Davis</wicri:regionArea></affiliation></author><author><name sortKey="Brown, C Titus" sort="Brown, C Titus" uniqKey="Brown C" first="C. Titus" last="Brown">C. Titus Brown</name><affiliation wicri:level="1"><nlm:aff id="aff1">Population Health and Reproduction, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Population Health and Reproduction, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff2">Genome Center, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Genome Center, University of California, Davis</wicri:regionArea></affiliation></author><author><name sortKey="Hormozdiari, Fereydoun" sort="Hormozdiari, Fereydoun" uniqKey="Hormozdiari F" first="Fereydoun" last="Hormozdiari">Fereydoun Hormozdiari</name><affiliation wicri:level="1"><nlm:aff id="aff2">Genome Center, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Genome Center, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3">MIND Institute, University of California, Davis, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>MIND Institute, University of California, Davis</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4">Biochemistry and Molecular Medicine, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Biochemistry and Molecular Medicine, University of California, Davis, 1 Shields Avenue, Davis, CA 95616</wicri:regionArea></affiliation></author></analytic><series><title level="j">iScience</title><idno type="eISSN">2589-0042</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Summary</title><p><italic>De novo</italic> genetic variants are an important source of causative variation in complex genetic disorders. Many methods for variant discovery rely on mapping reads to a reference genome, detecting numerous inherited variants irrelevant to the phenotype of interest. To distinguish between inherited and <italic>de novo</italic> variation, sequencing of families (parents and siblings) is commonly pursued. However, standard mapping-based approaches tend to have a high false-discovery rate for <italic>de novo</italic> variant prediction. Kevlar is a mapping-free method for <italic>de novo</italic> variant discovery, based on direct comparison of sequences between related individuals. Kevlar identifies high-abundance <italic>k</italic>-mers unique to the individual of interest. Reads containing these <italic>k</italic>-mers are partitioned into disjoint sets by shared <italic>k</italic>-mer content for variant calling, and preliminary variant predictions are sorted using a probabilistic score. We evaluated Kevlar on simulated and real datasets, demonstrating its ability to detect both <italic>de novo</italic> single-nucleotide variants and indels with high accuracy.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Bernardini, G" uniqKey="Bernardini G">G. Bernardini</name></author><author><name sortKey="Bonizzoni, P" uniqKey="Bonizzoni P">P. Bonizzoni</name></author><author><name sortKey="Denti, L" uniqKey="Denti L">L. Denti</name></author><author><name sortKey="Previtali, M" uniqKey="Previtali M">M. Previtali</name></author><author><name sortKey="Schonhuth, A" uniqKey="Schonhuth A">A. Schönhuth</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bray, N L" uniqKey="Bray N">N.L. Bray</name></author><author><name sortKey="Pimentel, H" uniqKey="Pimentel H">H. Pimentel</name></author><author><name sortKey="Melsted, P" uniqKey="Melsted P">P. 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Breitbart</name></author><author><name sortKey="Brown, K K" uniqKey="Brown K">K.K. Brown</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">iScience</journal-id><journal-id journal-id-type="iso-abbrev">iScience</journal-id><journal-title-group><journal-title>iScience</journal-title></journal-title-group><issn pub-type="epub">2589-0042</issn><publisher><publisher-name>Elsevier</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">31377530</article-id><article-id pub-id-type="pmc">6682328</article-id><article-id pub-id-type="publisher-id">S2589-0042(19)30259-7</article-id><article-id pub-id-type="doi">10.1016/j.isci.2019.07.032</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Kevlar: A Mapping-Free Framework for Accurate Discovery of <italic>De Novo</italic> Variants</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Standage</surname><given-names>Daniel S.</given-names></name><email>daniel.standage@nbacc.dhs.gov</email><xref rid="aff1" ref-type="aff">1</xref><xref rid="fn1" ref-type="fn">5</xref><xref rid="cor1" ref-type="corresp">∗</xref></contrib><contrib contrib-type="author"><name><surname>Brown</surname><given-names>C. Titus</given-names></name><email>ctbrown@ucdavis.edu</email><xref rid="aff1" ref-type="aff">1</xref><xref rid="aff2" ref-type="aff">2</xref><xref rid="cor2" ref-type="corresp">∗∗</xref></contrib><contrib contrib-type="author"><name><surname>Hormozdiari</surname><given-names>Fereydoun</given-names></name><email>fhormozd@ucdavis.edu</email><xref rid="aff2" ref-type="aff">2</xref><xref rid="aff3" ref-type="aff">3</xref><xref rid="aff4" ref-type="aff">4</xref><xref rid="fn2" ref-type="fn">6</xref><xref rid="cor3" ref-type="corresp">∗∗∗</xref></contrib></contrib-group><aff id="aff1"><label>1</label>Population Health and Reproduction, University of California, Davis, USA</aff><aff id="aff2"><label>2</label>Genome Center, University of California, Davis, USA</aff><aff id="aff3"><label>3</label>MIND Institute, University of California, Davis, USA</aff><aff id="aff4"><label>4</label>Biochemistry and Molecular Medicine, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA</aff><author-notes><corresp id="cor1"><label>∗</label>Corresponding author <email>daniel.standage@nbacc.dhs.gov</email></corresp><corresp id="cor2"><label>∗∗</label>Corresponding author <email>ctbrown@ucdavis.edu</email></corresp><corresp id="cor3"><label>∗∗∗</label>Corresponding author <email>fhormozd@ucdavis.edu</email></corresp><fn id="fn1"><label>5</label><p id="ntpara0010">Present address: National Biodefense Analysis and Countermeasures Center, Fort Detrick, MD 21702, USA</p></fn><fn id="fn2"><label>6</label><p id="ntpara0015">Lead Contact</p></fn></author-notes><pub-date pub-type="pmc-release"><day>23</day><month>7</month><year>2019</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="collection"><day>30</day><month>8</month><year>2019</year></pub-date><pub-date pub-type="epub"><day>23</day><month>7</month><year>2019</year></pub-date><volume>18</volume><fpage>28</fpage><lpage>36</lpage><history><date date-type="received"><day>11</day><month>2</month><year>2019</year></date><date date-type="rev-recd"><day>24</day><month>6</month><year>2019</year></date><date date-type="accepted"><day>19</day><month>7</month><year>2019</year></date></history><permissions><copyright-statement>© 2019 The Authors</copyright-statement><copyright-year>2019</copyright-year><license license-type="CC BY-NC-ND" xlink:href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><license-p>This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).</license-p></license></permissions><abstract id="abs0010"><title>Summary</title><p><italic>De novo</italic> genetic variants are an important source of causative variation in complex genetic disorders. Many methods for variant discovery rely on mapping reads to a reference genome, detecting numerous inherited variants irrelevant to the phenotype of interest. To distinguish between inherited and <italic>de novo</italic> variation, sequencing of families (parents and siblings) is commonly pursued. However, standard mapping-based approaches tend to have a high false-discovery rate for <italic>de novo</italic> variant prediction. Kevlar is a mapping-free method for <italic>de novo</italic> variant discovery, based on direct comparison of sequences between related individuals. Kevlar identifies high-abundance <italic>k</italic>-mers unique to the individual of interest. Reads containing these <italic>k</italic>-mers are partitioned into disjoint sets by shared <italic>k</italic>-mer content for variant calling, and preliminary variant predictions are sorted using a probabilistic score. We evaluated Kevlar on simulated and real datasets, demonstrating its ability to detect both <italic>de novo</italic> single-nucleotide variants and indels with high accuracy.</p></abstract><abstract abstract-type="graphical" id="abs0015"><title>Graphical Abstract</title><fig id="undfig1" position="anchor"><graphic xlink:href="fx1"></graphic></fig></abstract><abstract abstract-type="author-highlights" id="abs0020"><title>Highlights</title><p><list list-type="simple" id="ulist0010"><list-item id="u0010"><label>•</label><p id="p0010">Method for discovery of <italic>de novo</italic> variants without mapping reads to a reference genome</p></list-item><list-item id="u0015"><label>•</label><p id="p0015">Novel probabilistic score for ranking variant predictions as confidently <italic>de novo</italic></p></list-item><list-item id="u0020"><label>•</label><p id="p0020">Predicts <italic>de novo</italic> SNVs, indels, and structural variants with high accuracy</p></list-item><list-item id="u0025"><label>•</label><p id="p0025">Higher accuracy than competing methods for predicting long (>100 bp) variants</p></list-item></list></p></abstract><abstract abstract-type="teaser" id="abs0025"><p>Bioinformatics; Biological Sciences; Genetics</p></abstract><kwd-group id="kwrds0010"><title>Subject Areas</title><kwd>Bioinformatics</kwd><kwd>Biological Sciences</kwd><kwd>Genetics</kwd></kwd-group></article-meta><notes><p id="misc0010">Published: August 30, 2019</p></notes></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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