MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample
Identifieur interne : 001295 ( Pmc/Checkpoint ); précédent : 001294; suivant : 001296MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample
Auteurs : Yi Wang ; Henry C. M. Leung ; S. M. Yiu ; Francis Y. L. ChinSource :
- Bioinformatics [ 1367-4803 ] ; 2012.
Abstract
Url:
DOI: 10.1093/bioinformatics/bts397
PubMed: 22962452
PubMed Central: 3436824
Affiliations:
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<author><name sortKey="Wang, Yi" sort="Wang, Yi" uniqKey="Wang Y" first="Yi" last="Wang">Yi Wang</name>
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<author><name sortKey="Leung, Henry C M" sort="Leung, Henry C M" uniqKey="Leung H" first="Henry C. M." last="Leung">Henry C. M. Leung</name>
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<author><name sortKey="Yiu, S M" sort="Yiu, S M" uniqKey="Yiu S" first="S. M." last="Yiu">S. M. Yiu</name>
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<author><name sortKey="Chin, Francis Y L" sort="Chin, Francis Y L" uniqKey="Chin F" first="Francis Y. L." last="Chin">Francis Y. L. Chin</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample</title>
<author><name sortKey="Wang, Yi" sort="Wang, Yi" uniqKey="Wang Y" first="Yi" last="Wang">Yi Wang</name>
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<author><name sortKey="Leung, Henry C M" sort="Leung, Henry C M" uniqKey="Leung H" first="Henry C. M." last="Leung">Henry C. M. Leung</name>
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<author><name sortKey="Yiu, S M" sort="Yiu, S M" uniqKey="Yiu S" first="S. M." last="Yiu">S. M. Yiu</name>
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<author><name sortKey="Chin, Francis Y L" sort="Chin, Francis Y L" uniqKey="Chin F" first="Francis Y. L." last="Chin">Francis Y. L. Chin</name>
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<series><title level="j">Bioinformatics</title>
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<front><div type="abstract" xml:lang="en"><p><bold>Motivation:</bold>
Metagenomic binning remains an important topic in metagenomic analysis. Existing unsupervised binning methods for next-generation sequencing (NGS) reads do not perform well on (i) samples with low-abundance species or (ii) samples (even with high abundance) when there are many extremely low-abundance species. These two problems are common for real metagenomic datasets. Binning methods that can solve these problems are desirable.</p>
<p><bold>Results:</bold>
We proposed a two-round binning method (MetaCluster 5.0) that aims at identifying both low-abundance and high-abundance species in the presence of a large amount of noise due to many extremely low-abundance species. In summary, MetaCluster 5.0 uses a filtering strategy to remove noise from the extremely low-abundance species. It separate reads of high-abundance species from those of low-abundance species in two different rounds. To overcome the issue of low coverage for low-abundance species, multiple <italic>w</italic>
values are used to group reads with overlapping <italic>w</italic>
-mers, whereas reads from high-abundance species are grouped with high confidence based on a large <italic>w</italic>
and then binning expands to low-abundance species using a relaxed (shorter) <italic>w</italic>
. Compared to the recent tools, TOSS and MetaCluster 4.0, MetaCluster 5.0 can find more species (especially those with low abundance of say 6× to 10×) and can achieve better sensitivity and specificity using less memory and running time.</p>
<p><bold>Availability:</bold>
<ext-link ext-link-type="uri" xlink:href="http://i.cs.hku.hk/~alse/MetaCluster/">http://i.cs.hku.hk/~alse/MetaCluster/</ext-link>
</p>
<p><bold>Contact:</bold>
<email>chin@cs.hku.hk</email>
</p>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Amann, R I" uniqKey="Amann R">R.I. Amann</name>
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<biblStruct><analytic><author><name sortKey="Brady, A" uniqKey="Brady A">A. Brady</name>
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<author><name sortKey="Salzberg, S L" uniqKey="Salzberg S">S.L. Salzberg</name>
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<biblStruct><analytic><author><name sortKey="Kent, W J" uniqKey="Kent W">W.J. Kent</name>
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<biblStruct><analytic><author><name sortKey="Khachatryan, Z A" uniqKey="Khachatryan Z">Z.A. Khachatryan</name>
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<biblStruct><analytic><author><name sortKey="Tanaseichuk, O" uniqKey="Tanaseichuk O">O. Tanaseichuk</name>
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<biblStruct><analytic><author><name sortKey="Wang, Y" uniqKey="Wang Y">Y. Wang</name>
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<biblStruct><analytic><author><name sortKey="Wu, Y W" uniqKey="Wu Y">Y.W. Wu</name>
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<author><name sortKey="Ye, Y" uniqKey="Ye Y">Y. Ye</name>
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<biblStruct><analytic><author><name sortKey="Yang, B" uniqKey="Yang B">B. Yang</name>
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<biblStruct><analytic><author><name sortKey="Yang, B" uniqKey="Yang B">B. Yang</name>
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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">Bioinformatics</journal-id>
<journal-id journal-id-type="iso-abbrev">Bioinformatics</journal-id>
<journal-id journal-id-type="publisher-id">bioinformatics</journal-id>
<journal-id journal-id-type="hwp">bioinfo</journal-id>
<journal-title-group><journal-title>Bioinformatics</journal-title>
</journal-title-group>
<issn pub-type="ppub">1367-4803</issn>
<issn pub-type="epub">1367-4811</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">22962452</article-id>
<article-id pub-id-type="pmc">3436824</article-id>
<article-id pub-id-type="doi">10.1093/bioinformatics/bts397</article-id>
<article-id pub-id-type="publisher-id">bts397</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Original Papers</subject>
<subj-group><subject>Sequencing and Sequence Analysis</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Wang</surname>
<given-names>Yi</given-names>
</name>
<xref ref-type="corresp" rid="COR1"><sup>*</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Leung</surname>
<given-names>Henry C.M.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Yiu</surname>
<given-names>S.M.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Chin</surname>
<given-names>Francis Y.L.</given-names>
</name>
<xref ref-type="corresp" rid="COR1"><sup>*</sup>
</xref>
</contrib>
</contrib-group>
<aff id="AFF1">Department of Computer Science, The University of Hong Kong, Hong Kong</aff>
<author-notes><corresp id="COR1">* To whom correspondence should be addressed.</corresp>
</author-notes>
<pub-date pub-type="ppub"><day>15</day>
<month>9</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="epub"><day>3</day>
<month>9</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>3</day>
<month>9</month>
<year>2012</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>28</volume>
<issue>18</issue>
<issue-title>ECCB 2012 PROCEEDINGS PAPERS COMMITTEE SEPTEMBER 9 TO SEPTEMBER 12, 2012, CONFERENCE CENTER BASEL, SWITZERLAND</issue-title>
<fpage>i356</fpage>
<lpage>i362</lpage>
<permissions><copyright-statement>© The Author(s) (2012). Published by Oxford University Press.</copyright-statement>
<copyright-year>2012</copyright-year>
<license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by/3.0"><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>
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/3.0">http://creativecommons.org/licenses/by/3.0</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<abstract><p><bold>Motivation:</bold>
Metagenomic binning remains an important topic in metagenomic analysis. Existing unsupervised binning methods for next-generation sequencing (NGS) reads do not perform well on (i) samples with low-abundance species or (ii) samples (even with high abundance) when there are many extremely low-abundance species. These two problems are common for real metagenomic datasets. Binning methods that can solve these problems are desirable.</p>
<p><bold>Results:</bold>
We proposed a two-round binning method (MetaCluster 5.0) that aims at identifying both low-abundance and high-abundance species in the presence of a large amount of noise due to many extremely low-abundance species. In summary, MetaCluster 5.0 uses a filtering strategy to remove noise from the extremely low-abundance species. It separate reads of high-abundance species from those of low-abundance species in two different rounds. To overcome the issue of low coverage for low-abundance species, multiple <italic>w</italic>
values are used to group reads with overlapping <italic>w</italic>
-mers, whereas reads from high-abundance species are grouped with high confidence based on a large <italic>w</italic>
and then binning expands to low-abundance species using a relaxed (shorter) <italic>w</italic>
. Compared to the recent tools, TOSS and MetaCluster 4.0, MetaCluster 5.0 can find more species (especially those with low abundance of say 6× to 10×) and can achieve better sensitivity and specificity using less memory and running time.</p>
<p><bold>Availability:</bold>
<ext-link ext-link-type="uri" xlink:href="http://i.cs.hku.hk/~alse/MetaCluster/">http://i.cs.hku.hk/~alse/MetaCluster/</ext-link>
</p>
<p><bold>Contact:</bold>
<email>chin@cs.hku.hk</email>
</p>
</abstract>
<counts><page-count count="7"></page-count>
</counts>
</article-meta>
</front>
</pmc>
<affiliations><list></list>
<tree><noCountry><name sortKey="Chin, Francis Y L" sort="Chin, Francis Y L" uniqKey="Chin F" first="Francis Y. L." last="Chin">Francis Y. L. Chin</name>
<name sortKey="Leung, Henry C M" sort="Leung, Henry C M" uniqKey="Leung H" first="Henry C. M." last="Leung">Henry C. M. Leung</name>
<name sortKey="Wang, Yi" sort="Wang, Yi" uniqKey="Wang Y" first="Yi" last="Wang">Yi Wang</name>
<name sortKey="Yiu, S M" sort="Yiu, S M" uniqKey="Yiu S" first="S. M." last="Yiu">S. M. Yiu</name>
</noCountry>
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