MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison
Identifieur interne : 000613 ( Pmc/Curation ); précédent : 000612; suivant : 000614MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison
Auteurs : Baoxing Song [République populaire de Chine] ; Xiaoquan Su [République populaire de Chine] ; Jian Xu [République populaire de Chine] ; Kang Ning [République populaire de Chine]Source :
- PLoS ONE [ 1932-6203 ] ; 2012.
Abstract
The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.
Url:
DOI: 10.1371/journal.pone.0048998
PubMed: 23145044
PubMed Central: 3493548
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Province</wicri:regionArea></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</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>The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Proctor, Gn" uniqKey="Proctor G">GN Proctor</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Jurkowski, A" uniqKey="Jurkowski A">A Jurkowski</name></author><author><name sortKey="Reid, Ah" uniqKey="Reid A">AH Reid</name></author><author><name sortKey="Labov, Jb" uniqKey="Labov J">JB Labov</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Ley, Re" uniqKey="Ley R">RE Ley</name></author><author><name sortKey="Lozupone, Ca" uniqKey="Lozupone C">CA Lozupone</name></author><author><name sortKey="Hamady, M" uniqKey="Hamady M">M Hamady</name></author><author><name sortKey="Knight, R" uniqKey="Knight R">R 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<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">23145044</article-id><article-id pub-id-type="pmc">3493548</article-id><article-id pub-id-type="publisher-id">PONE-D-12-12364</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0048998</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>Metagenomics</subject></subj-group></subj-group><subj-group><subject>Biological Data Management</subject></subj-group></subj-group><subj-group><subject>Ecology</subject></subj-group><subj-group><subject>Genomics</subject><subj-group><subject>Genome Databases</subject><subj-group><subject>Sequence Databases</subject></subj-group></subj-group><subj-group><subject>Metagenomics</subject></subj-group></subj-group><subj-group><subject>Microbiology</subject></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Computer Science</subject><subj-group><subject>Software Engineering</subject><subj-group><subject>Software Tools</subject></subj-group></subj-group></subj-group></article-categories><title-group><article-title>MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison</article-title><alt-title alt-title-type="running-head">MetaSee: Metagenomic Sample Visualization Tool</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Song</surname><given-names>Baoxing</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Su</surname><given-names>Xiaoquan</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Xu</surname><given-names>Jian</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ning</surname><given-names>Kang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>BioEnergy Genome Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong Province, People’s Republic of China</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong Province, People’s Republic of China</addr-line></aff><aff id="aff3"><label>3</label><addr-line>CAS Key Laboratory of Biofuels, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong Province, People’s Republic of China</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Badger</surname><given-names>Jonathan H.</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>J. Craig Venter Institute, United States of America</addr-line></aff><author-notes><corresp id="cor1">* E-mail: <email>albertnk@gmail.com</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: BS XS JX KN. Performed the experiments: BS XS. Analyzed the data: BS XS KN. Contributed reagents/materials/analysis tools: BS XS KN. Wrote the paper: BS XS JX KN.</p></fn></author-notes><pub-date pub-type="collection"><year>2012</year></pub-date><pub-date pub-type="epub"><day>8</day><month>11</month><year>2012</year></pub-date><volume>7</volume><issue>11</issue><elocation-id>e48998</elocation-id><history><date date-type="received"><day>26</day><month>4</month><year>2012</year></date><date date-type="accepted"><day>3</day><month>10</month><year>2012</year></date></history><permissions><copyright-year>2012</copyright-year><copyright-holder>Song 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><p>The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.</p></abstract><funding-group><funding-statement>This work is partly supported by Chinese Academy of Sciences’ e-Science grant INFO-115-D01-Z006, Ministry of Science and Technology’s high-tech (863) grant 2009AA02Z310, and Natural Science Foundation of China grant 61103167. 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></record>Pour manipuler ce document sous Unix (Dilib)
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