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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
. </pmc-comment>
<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>
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