PeakRanger: A cloud-enabled peak caller for ChIP-seq data
Identifieur interne : 000278 ( Pmc/Curation ); précédent : 000277; suivant : 000279PeakRanger: A cloud-enabled peak caller for ChIP-seq data
Auteurs : Xin Feng [États-Unis, Canada] ; Robert Grossman [États-Unis] ; Lincoln Stein [États-Unis, Canada]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2011.
Abstract
Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks.
In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project.
Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project:
Url:
DOI: 10.1186/1471-2105-12-139
PubMed: 21554709
PubMed Central: 3103446
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0A3</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21554709</idno><idno type="pmc">3103446</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103446</idno><idno type="RBID">PMC:3103446</idno><idno type="doi">10.1186/1471-2105-12-139</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">000278</idno><idno type="wicri:Area/Pmc/Curation">000278</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">PeakRanger: A cloud-enabled peak caller for ChIP-seq data</title><author><name sortKey="Feng, Xin" sort="Feng, Xin" uniqKey="Feng X" first="Xin" last="Feng">Xin Feng</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I2">Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I3">Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON M5G 0A3, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON M5G 0A3</wicri:regionArea></affiliation></author><author><name sortKey="Grossman, Robert" sort="Grossman, Robert" uniqKey="Grossman R" first="Robert" last="Grossman">Robert Grossman</name><affiliation wicri:level="1"><nlm:aff id="I4">Institute for Genomics & Systems Biology, The University of Chicago, Cummings Life Sciences Center 431A, 920 East 58th Street, Chicago, IL 60637, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Institute for Genomics & Systems Biology, The University of Chicago, Cummings Life Sciences Center 431A, 920 East 58th Street, Chicago, IL 60637</wicri:regionArea></affiliation></author><author><name sortKey="Stein, Lincoln" sort="Stein, Lincoln" uniqKey="Stein L" first="Lincoln" last="Stein">Lincoln Stein</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I2">Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I3">Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON M5G 0A3, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON M5G 0A3</wicri:regionArea></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks.</p></sec><sec><title>Results</title><p>In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project.</p></sec><sec><title>Conclusions</title><p>Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: <ext-link ext-link-type="uri" xlink:href="http://www.modencode.org/software/ranger/">http://www.modencode.org/software/ranger/</ext-link></p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Mikkelsen, Ts" uniqKey="Mikkelsen T">TS Mikkelsen</name></author><author><name sortKey="Ku, M" uniqKey="Ku M">M Ku</name></author><author><name sortKey="Jaffe, Db" uniqKey="Jaffe D">DB Jaffe</name></author><author><name sortKey="Issac, B" uniqKey="Issac B">B Issac</name></author><author><name sortKey="Lieberman, E" uniqKey="Lieberman E">E Lieberman</name></author><author><name sortKey="Giannoukos, G" uniqKey="Giannoukos G">G Giannoukos</name></author><author><name sortKey="Alvarez, P" uniqKey="Alvarez P">P Alvarez</name></author><author><name sortKey="Brockman, W" uniqKey="Brockman W">W Brockman</name></author><author><name sortKey="Kim, Tk" uniqKey="Kim T">TK 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id><journal-title-group><journal-title>BMC Bioinformatics</journal-title></journal-title-group><issn pub-type="epub">1471-2105</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21554709</article-id><article-id pub-id-type="pmc">3103446</article-id><article-id pub-id-type="publisher-id">1471-2105-12-139</article-id><article-id pub-id-type="doi">10.1186/1471-2105-12-139</article-id><article-categories><subj-group subj-group-type="heading"><subject>Software</subject></subj-group></article-categories><title-group><article-title>PeakRanger: A cloud-enabled peak caller for ChIP-seq data</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Feng</surname><given-names>Xin</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref><email>drestion@gmail.com</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Grossman</surname><given-names>Robert</given-names></name><xref ref-type="aff" rid="I4">4</xref><email>grossman@labcomputing.org</email></contrib><contrib contrib-type="author" corresp="yes" id="A3"><name><surname>Stein</surname><given-names>Lincoln</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref><email>lincoln.stein@gmail.com</email></contrib></contrib-group><aff id="I1"><label>1</label>Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA</aff><aff id="I2"><label>2</label>Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA</aff><aff id="I3"><label>3</label>Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON M5G 0A3, Canada</aff><aff id="I4"><label>4</label>Institute for Genomics & Systems Biology, The University of Chicago, Cummings Life Sciences Center 431A, 920 East 58th Street, Chicago, IL 60637, USA</aff><pub-date pub-type="collection"><year>2011</year></pub-date><pub-date pub-type="epub"><day>9</day><month>5</month><year>2011</year></pub-date><volume>12</volume><fpage>139</fpage><lpage>139</lpage><history><date date-type="received"><day>14</day><month>1</month><year>2011</year></date><date date-type="accepted"><day>9</day><month>5</month><year>2011</year></date></history><permissions><copyright-statement>Copyright ©2011 Feng et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2011</copyright-year><copyright-holder>Feng et al; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0"><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/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2105/12/139"></self-uri><abstract><sec><title>Background</title><p>Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks.</p></sec><sec><title>Results</title><p>In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project.</p></sec><sec><title>Conclusions</title><p>Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: <ext-link ext-link-type="uri" xlink:href="http://www.modencode.org/software/ranger/">http://www.modencode.org/software/ranger/</ext-link></p></sec></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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