TCW: Transcriptome Computational Workbench
Identifieur interne : 000426 ( Ncbi/Merge ); précédent : 000425; suivant : 000427TCW: Transcriptome Computational Workbench
Auteurs : Carol Soderlund [États-Unis] ; William Nelson [États-Unis] ; Mark Willer [États-Unis] ; David R. Gang [États-Unis]Source :
- PLoS ONE [ 1932-6203 ] ; 2013.
Abstract
The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility.
The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results.
It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from
Url:
DOI: 10.1371/journal.pone.0069401
PubMed: 23874959
PubMed Central: 3714256
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PMC:3714256Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility.</p>
</sec>
<sec><title>Methodology</title>
<p>The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results.</p>
</sec>
<sec><title>Conclusion</title>
<p>It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from <ext-link ext-link-type="uri" xlink:href="http://www.agcol.arizona.edu/software/tcw">www.agcol.arizona.edu/software/tcw</ext-link>
.</p>
</sec>
</div>
</front>
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</author>
<author><name sortKey="Blattner, Fr" uniqKey="Blattner F">FR Blattner</name>
</author>
<author><name sortKey="Perna, Nt" uniqKey="Perna N">NT Perna</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Soderlund, C" uniqKey="Soderlund C">C Soderlund</name>
</author>
<author><name sortKey="Bomhoff, M" uniqKey="Bomhoff M">M Bomhoff</name>
</author>
<author><name sortKey="Nelson, Wm" uniqKey="Nelson W">WM Nelson</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Theocharidis, A" uniqKey="Theocharidis A">A Theocharidis</name>
</author>
<author><name sortKey="Van Dongen, S" uniqKey="Van Dongen S">S van Dongen</name>
</author>
<author><name sortKey="Enright, Aj" uniqKey="Enright A">AJ Enright</name>
</author>
<author><name sortKey="Freeman, Tc" uniqKey="Freeman T">TC Freeman</name>
</author>
</analytic>
</biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group><journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher><publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">23874959</article-id>
<article-id pub-id-type="pmc">3714256</article-id>
<article-id pub-id-type="publisher-id">PONE-D-13-15597</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0069401</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Biology</subject>
<subj-group><subject>Computational Biology</subject>
<subj-group><subject>Genomics</subject>
<subj-group><subject>Genome Analysis Tools</subject>
<subj-group><subject>Transcriptomes</subject>
</subj-group>
</subj-group>
<subj-group><subject>Comparative Genomics</subject>
<subject>Genome Expression Analysis</subject>
</subj-group>
</subj-group>
<subj-group><subject>Biological Data Management</subject>
</subj-group>
</subj-group>
<subj-group><subject>Genomics</subject>
<subj-group><subject>Genome Analysis Tools</subject>
<subj-group><subject>Transcriptomes</subject>
</subj-group>
</subj-group>
<subj-group><subject>Comparative Genomics</subject>
</subj-group>
</subj-group>
<subj-group><subject>Plant Science</subject>
<subj-group><subject>Plant Genomics</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Computer Science</subject>
<subj-group><subject>Software Engineering</subject>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Engineering</subject>
<subj-group><subject>Software Engineering</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>TCW: Transcriptome Computational Workbench</article-title>
<alt-title alt-title-type="running-head">Transcriptome Computational Workbench</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Soderlund</surname>
<given-names>Carol</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<xref ref-type="corresp" rid="cor1"><sup>*</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Nelson</surname>
<given-names>William</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Willer</surname>
<given-names>Mark</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gang</surname>
<given-names>David R.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label>
<addr-line>BIO5 Institute, University of Arizona, Tucson, Arizona, United States of America</addr-line>
</aff>
<aff id="aff2"><label>2</label>
<addr-line>Washington State University, Pullman, Washington, United States of America</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Candela</surname>
<given-names>Hector</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Universidad Miguel Hernández de Elche, Spain</addr-line>
</aff>
<author-notes><corresp id="cor1">* E-mail: <email>cari@agcol.arizona.edu</email>
</corresp>
<fn fn-type="conflict"><p><bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con"><p>Conceived and designed the experiments: CS DRG. Analyzed the data: CS WN. Contributed reagents/materials/analysis tools: DRG. Wrote the paper: CS. Designed the software: CS. Software development: CS WN MW.</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><year>2013</year>
</pub-date>
<pub-date pub-type="epub"><day>17</day>
<month>7</month>
<year>2013</year>
</pub-date>
<volume>8</volume>
<issue>7</issue>
<elocation-id>e69401</elocation-id>
<history><date date-type="received"><day>15</day>
<month>4</month>
<year>2013</year>
</date>
<date date-type="accepted"><day>7</day>
<month>6</month>
<year>2013</year>
</date>
</history>
<permissions><copyright-year>2013</copyright-year>
<copyright-holder>Soderlund et al</copyright-holder>
<license><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract><sec><title>Background</title>
<p>The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility.</p>
</sec>
<sec><title>Methodology</title>
<p>The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results.</p>
</sec>
<sec><title>Conclusion</title>
<p>It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from <ext-link ext-link-type="uri" xlink:href="http://www.agcol.arizona.edu/software/tcw">www.agcol.arizona.edu/software/tcw</ext-link>
.</p>
</sec>
</abstract>
<funding-group><funding-statement>This work was supported by National Science Foundation grant IOS-1044821 (<ext-link ext-link-type="uri" xlink:href="http://www.nsf.gov/awardsearch/showAward?AWD_ID=1044821">http://www.nsf.gov/awardsearch/showAward?AWD_ID=1044821</ext-link>
). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts><page-count count="10"></page-count>
</counts>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Arizona</li>
<li>Washington (État)</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Arizona"><name sortKey="Soderlund, Carol" sort="Soderlund, Carol" uniqKey="Soderlund C" first="Carol" last="Soderlund">Carol Soderlund</name>
</region>
<name sortKey="Gang, David R" sort="Gang, David R" uniqKey="Gang D" first="David R." last="Gang">David R. Gang</name>
<name sortKey="Nelson, William" sort="Nelson, William" uniqKey="Nelson W" first="William" last="Nelson">William Nelson</name>
<name sortKey="Willer, Mark" sort="Willer, Mark" uniqKey="Willer M" first="Mark" last="Willer">Mark Willer</name>
</country>
</tree>
</affiliations>
</record>
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