Konnector v2.0: pseudo-long reads from paired-end sequencing data
Identifieur interne : 000959 ( Pmc/Curation ); précédent : 000958; suivant : 000960Konnector v2.0: pseudo-long reads from paired-end sequencing data
Auteurs : Benjamin P. Vandervalk [Canada] ; Chen Yang [Canada] ; Zhuyi Xue [Canada] ; Karthika Raghavan [Canada] ; Justin Chu [Canada] ; Hamid Mohamadi [Canada] ; Shaun D. Jackman [Canada] ; Readman Chiu [Canada] ; René L. Warren [Canada] ; Inanç Birol [Canada]Source :
- BMC Medical Genomics [ 1755-8794 ] ; 2015.
Abstract
Reading the nucleotides from two ends of a DNA fragment is called paired-end tag (PET) sequencing. When the fragment length is longer than the combined read length, there remains a gap of unsequenced nucleotides between read pairs. If the target in such experiments is sequenced at a level to provide redundant coverage, it may be possible to bridge these gaps using bioinformatics methods. Konnector is a local
Konnector uses a probabilistic and memory-efficient data structure called Bloom filter to represent a k-mer spectrum - all possible sequences of length k in an input file, such as the collection of reads in a PET sequencing experiment. It performs look-ups to this data structure to construct an implicit de Bruijn graph, which describes (k-1) base pair overlaps between adjacent k-mers. It traverses this graph to bridge the gap between a given pair of flanking sequences.
Here we report the performance of Konnector v2.0 on simulated and experimental datasets, and compare it against other tools with similar functionality. We note that, representing k-mers with 1.5 bytes of memory on average, Konnector can scale to very large genomes. With our parallel implementation, it can also process over a billion bases on commodity hardware.
Url:
DOI: 10.1186/1755-8794-8-S3-S1
PubMed: 26399504
PubMed Central: 4582294
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Reading the nucleotides from two ends of a DNA fragment is called paired-end tag (PET) sequencing. When the fragment length is longer than the combined read length, there remains a gap of unsequenced nucleotides between read pairs. If the target in such experiments is sequenced at a level to provide redundant coverage, it may be possible to bridge these gaps using bioinformatics methods. Konnector is a local <italic>de novo </italic>
assembly tool that addresses this problem. Here we report on version 2.0 of our tool.</p>
</sec>
<sec><title>Results</title>
<p>Konnector uses a probabilistic and memory-efficient data structure called Bloom filter to represent a k-mer spectrum - all possible sequences of length k in an input file, such as the collection of reads in a PET sequencing experiment. It performs look-ups to this data structure to construct an implicit de Bruijn graph, which describes (k-1) base pair overlaps between adjacent k-mers. It traverses this graph to bridge the gap between a given pair of flanking sequences.</p>
</sec>
<sec><title>Conclusions</title>
<p>Here we report the performance of Konnector v2.0 on simulated and experimental datasets, and compare it against other tools with similar functionality. We note that, representing k-mers with 1.5 bytes of memory on average, Konnector can scale to very large genomes. With our parallel implementation, it can also process over a billion bases on commodity hardware.</p>
</sec>
</div>
</front>
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<pmc article-type="research-article" xml:lang="en"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Med Genomics</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Med Genomics</journal-id>
<journal-title-group><journal-title>BMC Medical Genomics</journal-title>
</journal-title-group>
<issn pub-type="epub">1755-8794</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">26399504</article-id>
<article-id pub-id-type="pmc">4582294</article-id>
<article-id pub-id-type="publisher-id">1755-8794-8-S3-S1</article-id>
<article-id pub-id-type="doi">10.1186/1755-8794-8-S3-S1</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research</subject>
</subj-group>
</article-categories>
<title-group><article-title>Konnector v2.0: pseudo-long reads from paired-end sequencing data</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" id="A1"><name><surname>Vandervalk</surname>
<given-names>Benjamin P</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>benv@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A2"><name><surname>Yang</surname>
<given-names>Chen</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>cheny@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A3"><name><surname>Xue</surname>
<given-names>Zhuyi</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>zxue@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A4"><name><surname>Raghavan</surname>
<given-names>Karthika</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>kraghavan@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A5"><name><surname>Chu</surname>
<given-names>Justin</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>cjustin@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A6"><name><surname>Mohamadi</surname>
<given-names>Hamid</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>hmohamadi@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A7"><name><surname>Jackman</surname>
<given-names>Shaun D</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>sjackman@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A8"><name><surname>Chiu</surname>
<given-names>Readman</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>rchiu@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" id="A9"><name><surname>Warren</surname>
<given-names>René L</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>rwarren@bcgsc.ca</email>
</contrib>
<contrib contrib-type="author" corresp="yes" id="A10"><name><surname>Birol</surname>
<given-names>Inanç</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>ibirol@bcgsc.ca</email>
</contrib>
</contrib-group>
<aff id="I1"><label>1</label>
Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada</aff>
<pub-date pub-type="collection"><year>2015</year>
</pub-date>
<pub-date pub-type="epub"><day>23</day>
<month>9</month>
<year>2015</year>
</pub-date>
<volume>8</volume>
<issue>Suppl 3</issue>
<supplement><named-content content-type="supplement-title">Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2014): Medical Genomics</named-content>
<named-content content-type="supplement-editor">Feng Luo</named-content>
<named-content content-type="supplement-sponsor">Publication of this supplement has not been supported by sponsorship. Information about the source of funding for the publication charges can be found in the individual articles. Articles have undergone the journal's standard peer review process for supplements. The Supplement Editor declares that they have no competing interests.</named-content>
</supplement>
<fpage>S1</fpage>
<lpage>S1</lpage>
<permissions><copyright-statement>Copyright © 2015 Vandervalk et al.;</copyright-statement>
<copyright-year>2015</copyright-year>
<copyright-holder>Vandervalk et al.;</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution 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 the original work is properly cited. 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>
<self-uri xlink:href="http://www.biomedcentral.com/1755-8794/8/S3/S1"></self-uri>
<abstract><sec><title>Background</title>
<p>Reading the nucleotides from two ends of a DNA fragment is called paired-end tag (PET) sequencing. When the fragment length is longer than the combined read length, there remains a gap of unsequenced nucleotides between read pairs. If the target in such experiments is sequenced at a level to provide redundant coverage, it may be possible to bridge these gaps using bioinformatics methods. Konnector is a local <italic>de novo </italic>
assembly tool that addresses this problem. Here we report on version 2.0 of our tool.</p>
</sec>
<sec><title>Results</title>
<p>Konnector uses a probabilistic and memory-efficient data structure called Bloom filter to represent a k-mer spectrum - all possible sequences of length k in an input file, such as the collection of reads in a PET sequencing experiment. It performs look-ups to this data structure to construct an implicit de Bruijn graph, which describes (k-1) base pair overlaps between adjacent k-mers. It traverses this graph to bridge the gap between a given pair of flanking sequences.</p>
</sec>
<sec><title>Conclusions</title>
<p>Here we report the performance of Konnector v2.0 on simulated and experimental datasets, and compare it against other tools with similar functionality. We note that, representing k-mers with 1.5 bytes of memory on average, Konnector can scale to very large genomes. With our parallel implementation, it can also process over a billion bases on commodity hardware.</p>
</sec>
</abstract>
<kwd-group><kwd>Bloom filter</kwd>
<kwd>de Bruijn graph</kwd>
<kwd>paired-end sequencing</kwd>
<kwd><italic>de novo </italic>
</kwd>
<kwd>genome assembly</kwd>
</kwd-group>
<conference><conf-date>2-5 November 2014</conf-date>
<conf-name>IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2014)</conf-name>
<conf-loc>Belfast, UK</conf-loc>
</conference>
</article-meta>
</front>
</pmc>
</record>
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