Co-expression tools for plant biology: opportunities for hypothesis generation and caveats
Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene...
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| Veröffentlicht in: | Plant, cell and environment Jg. 32; H. 12; S. 1633 - 1651 |
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| Hauptverfasser: | , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Oxford, UK
Oxford, UK : Blackwell Publishing Ltd
01.12.2009
Blackwell Publishing Ltd Blackwell |
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| ISSN: | 0140-7791, 1365-3040, 1365-3040 |
| Online-Zugang: | Volltext |
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| Abstract | Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology. |
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| AbstractList | Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology. Gene co‐expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co‐expression analysis asks the question ‘what are the genes that are co‐expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?’. Genes that are highly co‐expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co‐expression results, calculation of co‐expression scores and P values, and the influence of data sets used for co‐expression analysis. Finally, examples from the literature will be presented, wherein co‐expression has been used to corroborate and discover various aspects of plant biology. Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology.Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology. ABSTRACT Gene co‐expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co‐expression analysis asks the question ‘what are the genes that are co‐expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?’. Genes that are highly co‐expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co‐expression results, calculation of co‐expression scores and P values, and the influence of data sets used for co‐expression analysis. Finally, examples from the literature will be presented, wherein co‐expression has been used to corroborate and discover various aspects of plant biology. |
| Author | USADEL, BJÖRN OBAYASHI, TAKESHI TANIMOTO, MIMI PROVART, NICHOLAS J MUTWIL, MAREK CHOW, AMANDA PERSSON, STAFFAN GIORGI, FEDERICO M BASSEL, GEORGE W STEINHAUSER, DIRK |
| Author_xml | – sequence: 1 fullname: USADEL, BJÖRN – sequence: 2 fullname: OBAYASHI, TAKESHI – sequence: 3 fullname: MUTWIL, MAREK – sequence: 4 fullname: GIORGI, FEDERICO M – sequence: 5 fullname: BASSEL, GEORGE W – sequence: 6 fullname: TANIMOTO, MIMI – sequence: 7 fullname: CHOW, AMANDA – sequence: 8 fullname: STEINHAUSER, DIRK – sequence: 9 fullname: PERSSON, STAFFAN – sequence: 10 fullname: PROVART, NICHOLAS J |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22124379$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/19712066$$D View this record in MEDLINE/PubMed |
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| Snippet | Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the... ABSTRACT Gene co‐expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co‐expression analysis asks... Gene co‐expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co‐expression analysis asks the... |
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| SubjectTerms | Arabidopsis bioinformatics Biological and medical sciences Computational Biology correlation data collection Databases, Genetic Fundamental and applied biological sciences. Psychology gene expression Gene Expression Profiling Gene Expression Profiling - methods Gene Expression Profiling - statistics & numerical data genes Genes, Plant genetics methods Oligonucleotide Array Sequence Analysis Oligonucleotide Array Sequence Analysis - methods Oligonucleotide Array Sequence Analysis - statistics & numerical data plant biology Plants Plants - genetics prediction reverse genetics statistics & numerical data |
| Title | Co-expression tools for plant biology: opportunities for hypothesis generation and caveats |
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