OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees
Identifieur interne : 000666 ( Pmc/Curation ); précédent : 000665; suivant : 000667OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees
Auteurs : Song Gao [Singapour] ; Denis Bertrand [Singapour] ; Burton K. H. Chia [Singapour] ; Niranjan Nagarajan [Singapour]Source :
- Genome Biology [ 1474-7596 ] ; 2016.
Abstract
The assembly of large, repeat-rich eukaryotic genomes represents a significant challenge in genomics. While long-read technologies have made the high-quality assembly of small, microbial genomes increasingly feasible, data generation can be expensive for larger genomes. OPERA-LG is a scalable, exact algorithm for the scaffold assembly of large, repeat-rich genomes, out-performing state-of-the-art programs for scaffold correctness and contiguity. It provides a rigorous framework for scaffolding of repetitive sequences and a systematic approach for combining data from different second-generation and third-generation sequencing technologies. OPERA-LG provides an avenue for systematic augmentation and improvement of thousands of existing draft eukaryotic genome assemblies.
The online version of this article (doi:10.1186/s13059-016-0951-y) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s13059-016-0951-y
PubMed: 27169502
PubMed Central: 4864936
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Song Gao<affiliation><nlm:aff id="Aff3">South Australian Health & Medical Research Institute, North Terrace, Adelaide, 5000 SA Australia</nlm:aff>
<wicri:noCountry code="subfield">5000 SA Australia</wicri:noCountry>
</affiliation>
Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>The assembly of large, repeat-rich eukaryotic genomes represents a significant challenge in genomics. While long-read technologies have made the high-quality assembly of small, microbial genomes increasingly feasible, data generation can be expensive for larger genomes. OPERA-LG is a scalable, exact algorithm for the scaffold assembly of large, repeat-rich genomes, out-performing state-of-the-art programs for scaffold correctness and contiguity. It provides a rigorous framework for scaffolding of repetitive sequences and a systematic approach for combining data from different second-generation and third-generation sequencing technologies. OPERA-LG provides an avenue for systematic augmentation and improvement of thousands of existing draft eukaryotic genome assemblies.</p>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s13059-016-0951-y) contains supplementary material, which is available to authorized users.</p>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Genome Biol</journal-id>
<journal-id journal-id-type="iso-abbrev">Genome Biol</journal-id>
<journal-title-group><journal-title>Genome Biology</journal-title>
</journal-title-group>
<issn pub-type="ppub">1474-7596</issn>
<issn pub-type="epub">1474-760X</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">27169502</article-id>
<article-id pub-id-type="pmc">4864936</article-id>
<article-id pub-id-type="publisher-id">951</article-id>
<article-id pub-id-type="doi">10.1186/s13059-016-0951-y</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Method</subject>
</subj-group>
</article-categories>
<title-group><article-title>OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Gao</surname>
<given-names>Song</given-names>
</name>
<address><email>song.gao@sahmri.com</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
<xref ref-type="aff" rid="Aff2"></xref>
<xref ref-type="aff" rid="Aff3"></xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes"><name><surname>Bertrand</surname>
<given-names>Denis</given-names>
</name>
<address><email>bertrandd@gis.a-star.edu.sg</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chia</surname>
<given-names>Burton K. H.</given-names>
</name>
<address><email>chiakhb@gis.a-star.edu.sg</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Nagarajan</surname>
<given-names>Niranjan</given-names>
</name>
<address><email>nagarajann@gis.a-star.edu.sg</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<aff id="Aff1"><label></label>
Computational and Systems Biology, Genome Institute of Singapore, Singapore, 138672 Singapore</aff>
<aff id="Aff2"><label></label>
NUS Graduate School for Integrative Sciences and Engineering, Singapore, 117456 Singapore</aff>
<aff id="Aff3"><label></label>
South Australian Health & Medical Research Institute, North Terrace, Adelaide, 5000 SA Australia</aff>
</contrib-group>
<pub-date pub-type="epub"><day>11</day>
<month>5</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>11</day>
<month>5</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection"><year>2016</year>
</pub-date>
<volume>17</volume>
<elocation-id>102</elocation-id>
<history><date date-type="received"><day>27</day>
<month>10</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>13</day>
<month>4</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>© Gao et al. 2016</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"><p>The assembly of large, repeat-rich eukaryotic genomes represents a significant challenge in genomics. While long-read technologies have made the high-quality assembly of small, microbial genomes increasingly feasible, data generation can be expensive for larger genomes. OPERA-LG is a scalable, exact algorithm for the scaffold assembly of large, repeat-rich genomes, out-performing state-of-the-art programs for scaffold correctness and contiguity. It provides a rigorous framework for scaffolding of repetitive sequences and a systematic approach for combining data from different second-generation and third-generation sequencing technologies. OPERA-LG provides an avenue for systematic augmentation and improvement of thousands of existing draft eukaryotic genome assemblies.</p>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s13059-016-0951-y) contains supplementary material, which is available to authorized users.</p>
</sec>
</abstract>
<funding-group><award-group><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100005049</institution-id>
<institution>Science and Engineering Research Council, Agency for Science, Technology and Research (SG)</institution>
</institution-wrap>
</funding-source>
<award-id>102 101 0025</award-id>
<principal-award-recipient><name><surname>Nagarajan</surname>
<given-names>Niranjan</given-names>
</name>
</principal-award-recipient>
</award-group>
<award-group><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100005606</institution-id>
<institution>Genome Institute of Singapore (SG)</institution>
</institution-wrap>
</funding-source>
<award-id>ARB</award-id>
<principal-award-recipient><name><surname>Nagarajan</surname>
<given-names>Niranjan</given-names>
</name>
</principal-award-recipient>
</award-group>
</funding-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2016</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
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