Clustering of reads with alignment-free measures and quality values
Identifieur interne : 000244 ( Pmc/Curation ); précédent : 000243; suivant : 000245Clustering of reads with alignment-free measures and quality values
Auteurs : Matteo Comin [Italie] ; Andrea Leoni [Italie] ; Michele Schimd [Italie]Source :
- Algorithms for Molecular Biology : AMB [ 1748-7188 ] ; 2015.
Abstract
The data volume generated by Next-Generation Sequencing (NGS) technologies is growing at a pace that is now challenging the storage and data processing capacities of modern computer systems. In this context an important aspect is the reduction of data complexity by collapsing redundant reads in a single cluster to improve the run time, memory requirements, and quality of post-processing steps like assembly and error correction. Several alignment-free measures, based on
Quality scores produced by NGS platforms are fundamental for various analysis of NGS data like reads mapping and error detection. Moreover future-generation sequencing platforms will produce long reads but with a large number of erroneous bases (up to 15
In this scenario it will be fundamental to exploit quality value information within the alignment-free framework. To the best of our knowledge this is the first study that incorporates quality value information and
Url:
DOI: 10.1186/s13015-014-0029-x
PubMed: 25691913
PubMed Central: 4331138
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Clustering of reads with alignment-free measures and quality values</title>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>The data volume generated by Next-Generation Sequencing (NGS) technologies is growing at a pace that is now challenging the storage and data processing capacities of modern computer systems. In this context an important aspect is the reduction of data complexity by collapsing redundant reads in a single cluster to improve the run time, memory requirements, and quality of post-processing steps like assembly and error correction. Several alignment-free measures, based on <italic>k</italic>
-mers counts, have been used to cluster reads.</p>
<p>Quality scores produced by NGS platforms are fundamental for various analysis of NGS data like reads mapping and error detection. Moreover future-generation sequencing platforms will produce long reads but with a large number of erroneous bases (up to 15 <italic>%</italic>
).</p>
</sec>
<sec><title>Results</title>
<p>In this scenario it will be fundamental to exploit quality value information within the alignment-free framework. To the best of our knowledge this is the first study that incorporates quality value information and <italic>k</italic>
-mers counts, in the context of alignment-free measures, for the comparison of reads data. Based on this principles, in this paper we present a family of alignment-free measures called <italic>D</italic>
<sup><italic>q</italic>
</sup>
-type. A set of experiments on simulated and real reads data confirms that the new measures are superior to other classical alignment-free statistics, especially when erroneous reads are considered. Also results on <italic>de novo</italic>
assembly and metagenomic reads classification show that the introduction of quality values improves over standard alignment-free measures. These statistics are implemented in a software called QCluster (http://www.dei.unipd.it/~ciompin/main/qcluster.html).</p>
</sec>
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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">Algorithms Mol Biol</journal-id>
<journal-id journal-id-type="iso-abbrev">Algorithms Mol Biol</journal-id>
<journal-title-group><journal-title>Algorithms for Molecular Biology : AMB</journal-title>
</journal-title-group>
<issn pub-type="epub">1748-7188</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">25691913</article-id>
<article-id pub-id-type="pmc">4331138</article-id>
<article-id pub-id-type="publisher-id">29</article-id>
<article-id pub-id-type="doi">10.1186/s13015-014-0029-x</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research</subject>
</subj-group>
</article-categories>
<title-group><article-title>Clustering of reads with alignment-free measures and quality values</article-title>
</title-group>
<contrib-group><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"><name><surname>Leoni</surname>
<given-names>Andrea</given-names>
</name>
<address><email>andrea.leoni@studenti.unipd.it</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Schimd</surname>
<given-names>Michele</given-names>
</name>
<address><email>schimdmi@dei.unipd.it</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<aff id="Aff1">Department of Information Engineering, University of Padova, Padova, Italy</aff>
</contrib-group>
<pub-date pub-type="epub"><day>28</day>
<month>1</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>28</day>
<month>1</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="collection"><year>2015</year>
</pub-date>
<volume>10</volume>
<elocation-id>4</elocation-id>
<history><date date-type="received"><day>19</day>
<month>11</month>
<year>2014</year>
</date>
<date date-type="accepted"><day>17</day>
<month>12</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-statement>© Comin et al.; licensee BioMed Central. 2015</copyright-statement>
<license license-type="open-access"><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 credited. 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>The data volume generated by Next-Generation Sequencing (NGS) technologies is growing at a pace that is now challenging the storage and data processing capacities of modern computer systems. In this context an important aspect is the reduction of data complexity by collapsing redundant reads in a single cluster to improve the run time, memory requirements, and quality of post-processing steps like assembly and error correction. Several alignment-free measures, based on <italic>k</italic>
-mers counts, have been used to cluster reads.</p>
<p>Quality scores produced by NGS platforms are fundamental for various analysis of NGS data like reads mapping and error detection. Moreover future-generation sequencing platforms will produce long reads but with a large number of erroneous bases (up to 15 <italic>%</italic>
).</p>
</sec>
<sec><title>Results</title>
<p>In this scenario it will be fundamental to exploit quality value information within the alignment-free framework. To the best of our knowledge this is the first study that incorporates quality value information and <italic>k</italic>
-mers counts, in the context of alignment-free measures, for the comparison of reads data. Based on this principles, in this paper we present a family of alignment-free measures called <italic>D</italic>
<sup><italic>q</italic>
</sup>
-type. A set of experiments on simulated and real reads data confirms that the new measures are superior to other classical alignment-free statistics, especially when erroneous reads are considered. Also results on <italic>de novo</italic>
assembly and metagenomic reads classification show that the introduction of quality values improves over standard alignment-free measures. These statistics are implemented in a software called QCluster (http://www.dei.unipd.it/~ciompin/main/qcluster.html).</p>
</sec>
</abstract>
<kwd-group xml:lang="en"><title>Keywords</title>
<kwd>Alignment-free measures</kwd>
<kwd>Reads quality values</kwd>
<kwd>Reads clustering</kwd>
</kwd-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2015</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
</record>
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