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KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

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KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

Auteurs : Daniel Mapleson [Royaume-Uni] ; Gonzalo Garcia Accinelli [Royaume-Uni] ; George Kettleborough [Royaume-Uni] ; Jonathan Wright [Royaume-Uni] ; Bernardo J. Clavijo [Royaume-Uni]

Source :

Bioinformatics [ 1367-4803 ] ; 2016.

RBID : PMC:5408915

Abstract

AbstractMotivation

De novo assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data benefits from high-quality input with high coverage. However, in practice, determining the quality and quantity of useful reads quickly and in a reference-free manner is not trivial. Gaining a better understanding of the WGS data, and how that data is utilized by assemblers, provides useful insights that can inform the assembly process and result in better assemblies.

Results

We present the K-mer Analysis Toolkit (KAT): a multi-purpose software toolkit for reference-free quality control (QC) of WGS reads and de novo genome assemblies, primarily via their k-mer frequencies and GC composition. KAT enables users to assess levels of errors, bias and contamination at various stages of the assembly process. In this paper we highlight KAT’s ability to provide valuable insights into assembly composition and quality of genome assemblies through pairwise comparison of k-mers present in both input reads and the assemblies.

Availability and Implementation

KAT is available under the GPLv3 license at: https://github.com/TGAC/KAT.

Supplementary information

Supplementary data are available at Bioinformatics online.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408915

DOI: 10.1093/bioinformatics/btw663
PubMed: 27797770
PubMed Central: 5408915

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<front><div type="abstract" xml:lang="en"><title>Abstract</title>
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<p><italic>De novo</italic>
 assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data benefits from high-quality input with high coverage. However, in practice, determining the quality and quantity of useful reads quickly and in a reference-free manner is not trivial. Gaining a better understanding of the WGS data, and how that data is utilized by assemblers, provides useful insights that can inform the assembly process and result in better assemblies.</p>
</sec>
<sec id="SA2"><title>Results</title>
<p>We present the K-mer Analysis Toolkit (KAT): a multi-purpose software toolkit for reference-free quality control (QC) of WGS reads and <italic>de novo</italic>
 genome assemblies, primarily via their k-mer frequencies and GC composition. KAT enables users to assess levels of errors, bias and contamination at various stages of the assembly process. In this paper we highlight KAT’s ability to provide valuable insights into assembly composition and quality of genome assemblies through pairwise comparison of k-mers present in both input reads and the assemblies.</p>
</sec>
<sec id="SA3"><title>Availability and Implementation</title>
<p>KAT is available under the GPLv3 license at: <ext-link ext-link-type="uri" xlink:href="https://github.com/TGAC/KAT">https://github.com/TGAC/KAT</ext-link>
.</p>
</sec>
<sec id="SA4"><title>Supplementary information</title>
<p><xref ref-type="supplementary-material" rid="sup1">Supplementary data</xref>
 are available at <italic>Bioinformatics</italic>
 online.</p>
</sec>
</div>
</front>
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  <front><journal-meta><journal-id journal-id-type="nlm-ta">Bioinformatics</journal-id>
<journal-id journal-id-type="iso-abbrev">Bioinformatics</journal-id>
<journal-id journal-id-type="publisher-id">bioinformatics</journal-id>
<journal-title-group><journal-title>Bioinformatics</journal-title>
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<issn pub-type="ppub">1367-4803</issn>
<issn pub-type="epub">1367-4811</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
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<article-id pub-id-type="doi">10.1093/bioinformatics/btw663</article-id>
<article-id pub-id-type="publisher-id">btw663</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Applications Notes</subject>
<subj-group subj-group-type="category-toc-heading"><subject>Sequence Analysis</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Mapleson</surname>
<given-names>Daniel</given-names>
</name>
<xref ref-type="aff" rid="btw663-aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Garcia Accinelli</surname>
<given-names>Gonzalo</given-names>
</name>
<xref ref-type="aff" rid="btw663-aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kettleborough</surname>
<given-names>George</given-names>
</name>
<xref ref-type="aff" rid="btw663-aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Wright</surname>
<given-names>Jonathan</given-names>
</name>
<xref ref-type="aff" rid="btw663-aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Clavijo</surname>
<given-names>Bernardo J</given-names>
</name>
<xref ref-type="corresp" rid="btw663-cor1"></xref>
<xref ref-type="aff" rid="btw663-aff1"></xref>
<pmc-comment>bernardo.clavijo@earlham.ac.uk</pmc-comment>
        </contrib>
</contrib-group>
<contrib-group><contrib contrib-type="editor"><name><surname>Berger</surname>
<given-names>Bonnie</given-names>
</name>
<role>Associate Editor</role>
</contrib>
</contrib-group>
<aff id="btw663-aff1">Earlham Institute, Norwich Research Park, Norwich, UK</aff>
<author-notes><corresp id="btw663-cor1">To whom correspondence should be addressed. Email: <email>bernardo.clavijo@earlham.ac.uk</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><day>15</day>
<month>2</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub" iso-8601-date="2016-11-28"><day>28</day>
<month>11</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>28</day>
<month>11</month>
<year>2016</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the . </pmc-comment>
      <volume>33</volume>
<issue>4</issue>
<fpage>574</fpage>
<lpage>576</lpage>
<history><date date-type="received"><day>19</day>
<month>7</month>
<year>2016</year>
</date>
<date date-type="rev-recd"><day>06</day>
<month>10</month>
<year>2016</year>
</date>
<date date-type="accepted"><day>17</day>
<month>10</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>© The Author 2016. Published by Oxford University Press.</copyright-statement>
<copyright-year>2016</copyright-year>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/" license-type="cc-by"><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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri xlink:href="btw663.pdf"></self-uri>
<abstract><title>Abstract</title>
<sec id="SA1"><title>Motivation</title>
<p><italic>De novo</italic>
 assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data benefits from high-quality input with high coverage. However, in practice, determining the quality and quantity of useful reads quickly and in a reference-free manner is not trivial. Gaining a better understanding of the WGS data, and how that data is utilized by assemblers, provides useful insights that can inform the assembly process and result in better assemblies.</p>
</sec>
<sec id="SA2"><title>Results</title>
<p>We present the K-mer Analysis Toolkit (KAT): a multi-purpose software toolkit for reference-free quality control (QC) of WGS reads and <italic>de novo</italic>
 genome assemblies, primarily via their k-mer frequencies and GC composition. KAT enables users to assess levels of errors, bias and contamination at various stages of the assembly process. In this paper we highlight KAT’s ability to provide valuable insights into assembly composition and quality of genome assemblies through pairwise comparison of k-mers present in both input reads and the assemblies.</p>
</sec>
<sec id="SA3"><title>Availability and Implementation</title>
<p>KAT is available under the GPLv3 license at: <ext-link ext-link-type="uri" xlink:href="https://github.com/TGAC/KAT">https://github.com/TGAC/KAT</ext-link>
.</p>
</sec>
<sec id="SA4"><title>Supplementary information</title>
<p><xref ref-type="supplementary-material" rid="sup1">Supplementary data</xref>
 are available at <italic>Bioinformatics</italic>
 online.</p>
</sec>
</abstract>
<funding-group><award-group award-type="grant"><funding-source><named-content content-type="funder-name">BBSRC, Institute Strategic Programme</named-content>
</funding-source>
<award-id>BB/J004669/1</award-id>
</award-group>
</funding-group>
<counts><page-count count="3"></page-count>
</counts>
</article-meta>
</front>
</pmc>
</record>

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KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

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Abstract

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