Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data.
Identifieur interne : 003C15 ( Main/Exploration ); précédent : 003C14; suivant : 003C16Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data.
Auteurs : Max Bylesjö [Suède] ; Daniel Eriksson ; Miyako Kusano ; Thomas Moritz ; Johan TryggSource :
- The Plant journal : for cell and molecular biology [ 0960-7412 ] ; 2007.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Plantes, Populus.
- métabolisme : Plantes, Populus.
- méthodes : Biologie des systèmes, Biologie informatique, Génomique, Protéomique.
- Analyse de régression, Analyse multifactorielle, Modèles biologiques.
English descriptors
- KwdEn :
- MESH :
- genetics : Plants, Populus.
- metabolism : Plants, Populus.
- methods : Computational Biology, Genomics, Proteomics, Systems Biology.
- Models, Biological, Multivariate Analysis, Regression Analysis.
Abstract
The technological advances in the instrumentation employed in life sciences have enabled the collection of a virtually unlimited quantity of data from multiple sources. By gathering data from several analytical platforms, with the aim of parallel monitoring of, e.g. transcriptomic, metabolomic or proteomic events, one hopes to answer and understand biological questions and observations. This 'systems biology' approach typically involves advanced statistics to facilitate the interpretation of the data. In the present study, we demonstrate that the O2PLS multivariate regression method can be used for combining 'omics' types of data. With this methodology, systematic variation that overlaps across analytical platforms can be separated from platform-specific systematic variation. A study of Populus tremula x Populus tremuloides, investigating short-day-induced effects at transcript and metabolite levels, is employed to demonstrate the benefits of the methodology. We show how the models can be validated and interpreted to identify biologically relevant events, and discuss the results in relation to a pairwise univariate correlation approach and principal component analysis.
DOI: 10.1111/j.1365-313X.2007.03293.x
PubMed: 17931352
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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sortKey="Moritz, Thomas" sort="Moritz, Thomas" uniqKey="Moritz T" first="Thomas" last="Moritz">Thomas Moritz</name></author><author><name sortKey="Trygg, Johan" sort="Trygg, Johan" uniqKey="Trygg J" first="Johan" last="Trygg">Johan Trygg</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2007">2007</date><idno type="RBID">pubmed:17931352</idno><idno type="pmid">17931352</idno><idno type="doi">10.1111/j.1365-313X.2007.03293.x</idno><idno type="wicri:Area/Main/Corpus">003A50</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">003A50</idno><idno type="wicri:Area/Main/Curation">003A50</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">003A50</idno><idno type="wicri:Area/Main/Exploration">003A50</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite 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sort="Trygg, Johan" uniqKey="Trygg J" first="Johan" last="Trygg">Johan Trygg</name></author></analytic><series><title level="j">The Plant journal : for cell and molecular biology</title><idno type="ISSN">0960-7412</idno><imprint><date when="2007" type="published">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computational Biology (methods)</term><term>Genomics (methods)</term><term>Models, Biological (MeSH)</term><term>Multivariate Analysis (MeSH)</term><term>Plants (genetics)</term><term>Plants (metabolism)</term><term>Populus (genetics)</term><term>Populus (metabolism)</term><term>Proteomics (methods)</term><term>Regression Analysis (MeSH)</term><term>Systems Biology (methods)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de régression (MeSH)</term><term>Analyse multifactorielle (MeSH)</term><term>Biologie des systèmes (méthodes)</term><term>Biologie informatique 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informatique</term><term>Génomique</term><term>Protéomique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Models, Biological</term><term>Multivariate Analysis</term><term>Regression Analysis</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de régression</term><term>Analyse multifactorielle</term><term>Modèles biologiques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The technological advances in the instrumentation employed in life sciences have enabled the collection of a virtually unlimited quantity of data from multiple sources. By gathering data from several analytical platforms, with the aim of parallel monitoring of, e.g. transcriptomic, metabolomic or proteomic events, one hopes to answer and understand biological questions and observations. This 'systems biology' approach typically involves advanced statistics to facilitate the interpretation of the data. In the present study, we demonstrate that the O2PLS multivariate regression method can be used for combining 'omics' types of data. With this methodology, systematic variation that overlaps across analytical platforms can be separated from platform-specific systematic variation. A study of Populus tremula x Populus tremuloides, investigating short-day-induced effects at transcript and metabolite levels, is employed to demonstrate the benefits of the methodology. 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By gathering data from several analytical platforms, with the aim of parallel monitoring of, e.g. transcriptomic, metabolomic or proteomic events, one hopes to answer and understand biological questions and observations. This 'systems biology' approach typically involves advanced statistics to facilitate the interpretation of the data. In the present study, we demonstrate that the O2PLS multivariate regression method can be used for combining 'omics' types of data. With this methodology, systematic variation that overlaps across analytical platforms can be separated from platform-specific systematic variation. A study of Populus tremula x Populus tremuloides, investigating short-day-induced effects at transcript and metabolite levels, is employed to demonstrate the benefits of the methodology. We show how the models can be validated and interpreted to identify biologically relevant events, and discuss the results in relation to a pairwise univariate correlation approach and principal component analysis.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Bylesjö</LastName><ForeName>Max</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Research group for Chemometrics, Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Eriksson</LastName><ForeName>Daniel</ForeName><Initials>D</Initials></Author><Author ValidYN="Y"><LastName>Kusano</LastName><ForeName>Miyako</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Moritz</LastName><ForeName>Thomas</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Trygg</LastName><ForeName>Johan</ForeName><Initials>J</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2007</Year><Month>10</Month><Day>10</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Plant J</MedlineTA><NlmUniqueID>9207397</NlmUniqueID><ISSNLinking>0960-7412</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D019295" MajorTopicYN="N">Computational Biology</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D023281" MajorTopicYN="N">Genomics</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="Y">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015999" MajorTopicYN="N">Multivariate Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010944" MajorTopicYN="N">Plants</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D040901" MajorTopicYN="N">Proteomics</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012044" MajorTopicYN="N">Regression Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D049490" MajorTopicYN="N">Systems Biology</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2007</Year><Month>10</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2008</Year><Month>3</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2007</Year><Month>10</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">17931352</ArticleId><ArticleId IdType="pii">TPJ3293</ArticleId><ArticleId IdType="doi">10.1111/j.1365-313X.2007.03293.x</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Suède</li></country></list><tree><noCountry><name sortKey="Eriksson, Daniel" sort="Eriksson, Daniel" uniqKey="Eriksson D" first="Daniel" last="Eriksson">Daniel Eriksson</name><name sortKey="Kusano, Miyako" sort="Kusano, Miyako" uniqKey="Kusano M" first="Miyako" last="Kusano">Miyako Kusano</name><name sortKey="Moritz, Thomas" sort="Moritz, Thomas" uniqKey="Moritz T" first="Thomas" last="Moritz">Thomas Moritz</name><name sortKey="Trygg, Johan" sort="Trygg, Johan" uniqKey="Trygg J" first="Johan" last="Trygg">Johan Trygg</name></noCountry><country name="Suède"><noRegion><name sortKey="Bylesjo, Max" sort="Bylesjo, Max" uniqKey="Bylesjo M" first="Max" last="Bylesjö">Max Bylesjö</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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