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ErmineJ: Tool for functional analysis of gene expression data sets

BACKGROUND: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for &quo...

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Detalles Bibliográficos
Autores principales: Lee, Homin K, Braynen, William, Keshav, Kiran, Pavlidis, Paul
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1310606/
https://www.ncbi.nlm.nih.gov/pubmed/16280084
http://dx.doi.org/10.1186/1471-2105-6-269
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author Lee, Homin K
Braynen, William
Keshav, Kiran
Pavlidis, Paul
author_facet Lee, Homin K
Braynen, William
Keshav, Kiran
Pavlidis, Paul
author_sort Lee, Homin K
collection PubMed
description BACKGROUND: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for "over-representation" of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported. RESULTS: We introduce ErmineJ, a multiplatform user-friendly stand-alone software tool for the analysis of functionally-relevant sets of genes in the context of microarray gene expression data. ErmineJ implements multiple algorithms for gene set analysis, including over-representation and resampling-based methods that focus on gene scores or correlation of gene expression profiles. In addition to a graphical user interface, ErmineJ has a command line interface and an application programming interface that can be used to automate analyses. The graphical user interface includes tools for creating and modifying gene sets, visualizing the Gene Ontology as a table or tree, and visualizing gene expression data. ErmineJ comes with a complete user manual, and is open-source software licensed under the Gnu Public License. CONCLUSION: The availability of multiple analysis algorithms, together with a rich feature set and simple graphical interface, should make ErmineJ a useful addition to the biologist's informatics toolbox. ErmineJ is available from .
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spelling pubmed-13106062005-12-10 ErmineJ: Tool for functional analysis of gene expression data sets Lee, Homin K Braynen, William Keshav, Kiran Pavlidis, Paul BMC Bioinformatics Software BACKGROUND: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for "over-representation" of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported. RESULTS: We introduce ErmineJ, a multiplatform user-friendly stand-alone software tool for the analysis of functionally-relevant sets of genes in the context of microarray gene expression data. ErmineJ implements multiple algorithms for gene set analysis, including over-representation and resampling-based methods that focus on gene scores or correlation of gene expression profiles. In addition to a graphical user interface, ErmineJ has a command line interface and an application programming interface that can be used to automate analyses. The graphical user interface includes tools for creating and modifying gene sets, visualizing the Gene Ontology as a table or tree, and visualizing gene expression data. ErmineJ comes with a complete user manual, and is open-source software licensed under the Gnu Public License. CONCLUSION: The availability of multiple analysis algorithms, together with a rich feature set and simple graphical interface, should make ErmineJ a useful addition to the biologist's informatics toolbox. ErmineJ is available from . BioMed Central 2005-11-09 /pmc/articles/PMC1310606/ /pubmed/16280084 http://dx.doi.org/10.1186/1471-2105-6-269 Text en Copyright © 2005 Lee et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Lee, Homin K
Braynen, William
Keshav, Kiran
Pavlidis, Paul
ErmineJ: Tool for functional analysis of gene expression data sets
title ErmineJ: Tool for functional analysis of gene expression data sets
title_full ErmineJ: Tool for functional analysis of gene expression data sets
title_fullStr ErmineJ: Tool for functional analysis of gene expression data sets
title_full_unstemmed ErmineJ: Tool for functional analysis of gene expression data sets
title_short ErmineJ: Tool for functional analysis of gene expression data sets
title_sort erminej: tool for functional analysis of gene expression data sets
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1310606/
https://www.ncbi.nlm.nih.gov/pubmed/16280084
http://dx.doi.org/10.1186/1471-2105-6-269
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