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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Estimating population diversity with CatchAll</title><author><name sortKey="Bunge, John" sort="Bunge, John" uniqKey="Bunge J" first="John" last="Bunge">John Bunge</name><affiliation><nlm:aff id="AFF1">Department of Statistical Science,</nlm:aff></affiliation></author><author><name sortKey="Woodard, Linda" sort="Woodard, Linda" uniqKey="Woodard L" first="Linda" last="Woodard">Linda Woodard</name><affiliation><nlm:aff id="AFF1">Center for Advanced Computing, Cornell University, Ithaca, NY 14853, USA,</nlm:aff></affiliation></author><author><name sortKey="Bohning, Dankmar" sort="Bohning, Dankmar" uniqKey="Bohning D" first="Dankmar" last="Böhning">Dankmar Böhning</name><affiliation><nlm:aff id="AFF1">School of Mathematics, University of Southampton, Southampton SO17 1BJ, UK,</nlm:aff></affiliation></author><author><name sortKey="Foster, James A" sort="Foster, James A" uniqKey="Foster J" first="James A." last="Foster">James A. Foster</name><affiliation><nlm:aff id="AFF1">Department of Biological Sciences, University of Idaho, Moscow, ID 83844,</nlm:aff></affiliation></author><author><name sortKey="Connolly, Sean" sort="Connolly, Sean" uniqKey="Connolly S" first="Sean" last="Connolly">Sean Connolly</name><affiliation><nlm:aff wicri:cut=" and" id="AFF1">Charles River Associates, Boston, MA 02116</nlm:aff></affiliation></author><author><name sortKey="Allen, Heather K" sort="Allen, Heather K" uniqKey="Allen H" first="Heather K." last="Allen">Heather K. Allen</name><affiliation><nlm:aff id="AFF1">Food Safety and Enteric Pathogens Research Unit, National Animal Disease Center, Agricultural Research Service, Ames, IA, 50010, USA</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22333246</idno><idno type="pmc">3315724</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315724</idno><idno type="RBID">PMC:3315724</idno><idno type="doi">10.1093/bioinformatics/bts075</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">000356</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Estimating population diversity with CatchAll</title><author><name sortKey="Bunge, John" sort="Bunge, John" uniqKey="Bunge J" first="John" last="Bunge">John Bunge</name><affiliation><nlm:aff id="AFF1">Department of Statistical Science,</nlm:aff></affiliation></author><author><name sortKey="Woodard, Linda" sort="Woodard, Linda" uniqKey="Woodard L" first="Linda" last="Woodard">Linda Woodard</name><affiliation><nlm:aff id="AFF1">Center for Advanced Computing, Cornell University, Ithaca, NY 14853, USA,</nlm:aff></affiliation></author><author><name sortKey="Bohning, Dankmar" sort="Bohning, Dankmar" uniqKey="Bohning D" first="Dankmar" last="Böhning">Dankmar Böhning</name><affiliation><nlm:aff id="AFF1">School of Mathematics, University of Southampton, Southampton SO17 1BJ, UK,</nlm:aff></affiliation></author><author><name sortKey="Foster, James A" sort="Foster, James A" uniqKey="Foster J" first="James A." last="Foster">James A. Foster</name><affiliation><nlm:aff id="AFF1">Department of Biological Sciences, University of Idaho, Moscow, ID 83844,</nlm:aff></affiliation></author><author><name sortKey="Connolly, Sean" sort="Connolly, Sean" uniqKey="Connolly S" first="Sean" last="Connolly">Sean Connolly</name><affiliation><nlm:aff wicri:cut=" and" id="AFF1">Charles River Associates, Boston, MA 02116</nlm:aff></affiliation></author><author><name sortKey="Allen, Heather K" sort="Allen, Heather K" uniqKey="Allen H" first="Heather K." last="Allen">Heather K. Allen</name><affiliation><nlm:aff id="AFF1">Food Safety and Enteric Pathogens Research Unit, National Animal Disease Center, Agricultural Research Service, Ames, IA, 50010, USA</nlm:aff></affiliation></author></analytic><series><title level="j">Bioinformatics</title><idno type="ISSN">1367-4803</idno><idno type="eISSN">1367-4811</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><bold>Motivation:</bold> The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or <italic>species richness</italic> in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments.</p><p><bold>Results:</bold> We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program.</p><p><bold>Availability:</bold> Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at <ext-link ext-link-type="uri" xlink:href="www.northeastern.edu/catchall">www.northeastern.edu/catchall</ext-link>.</p><p><bold>Contact:</bold><email>jab18@cornell.edu</email></p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<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">22333246</article-id><article-id pub-id-type="pmc">3315724</article-id><article-id pub-id-type="doi">10.1093/bioinformatics/bts075</article-id><article-id pub-id-type="publisher-id">bts075</article-id><article-categories><subj-group subj-group-type="heading"><subject>Applications Note</subject><subj-group><subject>Genetics and Population Analysis</subject></subj-group></subj-group></article-categories><title-group><article-title>Estimating population diversity with CatchAll</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Bunge</surname><given-names>John</given-names></name><xref ref-type="aff" rid="AFF1"><sup>1</sup></xref><xref ref-type="corresp" rid="COR1">*</xref></contrib><contrib contrib-type="author"><name><surname>Woodard</surname><given-names>Linda</given-names></name><xref ref-type="aff" rid="AFF1"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Böhning</surname><given-names>Dankmar</given-names></name><xref ref-type="aff" rid="AFF1"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Foster</surname><given-names>James A.</given-names></name><xref ref-type="aff" rid="AFF1"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Connolly</surname><given-names>Sean</given-names></name><xref ref-type="aff" rid="AFF1"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Allen</surname><given-names>Heather K.</given-names></name><xref ref-type="aff" rid="AFF1"><sup>6</sup></xref></contrib></contrib-group><aff id="AFF1"><sup>1</sup>Department of Statistical Science,<sup>2</sup>Center for Advanced Computing, Cornell University, Ithaca, NY 14853, USA,<sup>3</sup>School of Mathematics, University of Southampton, Southampton SO17 1BJ, UK,<sup>4</sup>Department of Biological Sciences, University of Idaho, Moscow, ID 83844,<sup>5</sup>Charles River Associates, Boston, MA 02116 and<sup>6</sup>Food Safety and Enteric Pathogens Research Unit, National Animal Disease Center, Agricultural Research Service, Ames, IA, 50010, USA</aff><author-notes><corresp id="COR1">* To whom correspondence should be addressed.</corresp><fn><p>Associate Editor: Jeffrey Barrett</p></fn></author-notes><pub-date pub-type="ppub"><day>1</day><month>4</month><year>2012</year></pub-date><pub-date pub-type="epub"><day>13</day><month>2</month><year>2012</year></pub-date><pub-date pub-type="pmc-release"><day>1</day><month>4</month><year>2013</year></pub-date><pmc-comment> PMC Release delay is 12 months and 0 days and was based on the
<volume>28</volume><issue>7</issue><fpage>1045</fpage><lpage>1047</lpage><history><date date-type="received"><day>1</day><month>12</month><year>2011</year></date><date date-type="rev-recd"><day>4</day><month>2</month><year>2012</year></date><date date-type="accepted"><day>6</day><month>2</month><year>2012</year></date></history><permissions><copyright-statement>© The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com</copyright-statement><copyright-year>2012</copyright-year></permissions><abstract><p><bold>Motivation:</bold> The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or <italic>species richness</italic> in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments.</p><p><bold>Results:</bold> We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program.</p><p><bold>Availability:</bold> Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at <ext-link ext-link-type="uri" xlink:href="www.northeastern.edu/catchall">www.northeastern.edu/catchall</ext-link>.</p><p><bold>Contact:</bold><email>jab18@cornell.edu</email></p></abstract><counts><page-count count="3"></page-count></counts></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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