Cargando…
Model-based gene set analysis for Bioconductor
Summary: Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant,...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117381/ https://www.ncbi.nlm.nih.gov/pubmed/21561920 http://dx.doi.org/10.1093/bioinformatics/btr296 |
_version_ | 1782206326138470400 |
---|---|
author | Bauer, Sebastian Robinson, Peter N. Gagneur, Julien |
author_facet | Bauer, Sebastian Robinson, Peter N. Gagneur, Julien |
author_sort | Bauer, Sebastian |
collection | PubMed |
description | Summary: Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant, which can complicate interpretation. We have recently developed an approach called model-based gene set analysis (MGSA), that substantially reduces the number of redundant categories returned by the gene-category analysis. In this work, we present the Bioconductor package mgsa, which makes the MGSA algorithm available to users of the R language. Our package provides a simple and flexible application programming interface for applying the approach. Availability: The mgsa package has been made available as part of Bioconductor 2.8. It is released under the conditions of the Artistic license 2.0. Contact: peter.robinson@charite.de; julien.gagneur@embl.de |
format | Online Article Text |
id | pubmed-3117381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31173812011-06-17 Model-based gene set analysis for Bioconductor Bauer, Sebastian Robinson, Peter N. Gagneur, Julien Bioinformatics Applications Note Summary: Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant, which can complicate interpretation. We have recently developed an approach called model-based gene set analysis (MGSA), that substantially reduces the number of redundant categories returned by the gene-category analysis. In this work, we present the Bioconductor package mgsa, which makes the MGSA algorithm available to users of the R language. Our package provides a simple and flexible application programming interface for applying the approach. Availability: The mgsa package has been made available as part of Bioconductor 2.8. It is released under the conditions of the Artistic license 2.0. Contact: peter.robinson@charite.de; julien.gagneur@embl.de Oxford University Press 2011-07-01 2011-05-10 /pmc/articles/PMC3117381/ /pubmed/21561920 http://dx.doi.org/10.1093/bioinformatics/btr296 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Bauer, Sebastian Robinson, Peter N. Gagneur, Julien Model-based gene set analysis for Bioconductor |
title | Model-based gene set analysis for Bioconductor |
title_full | Model-based gene set analysis for Bioconductor |
title_fullStr | Model-based gene set analysis for Bioconductor |
title_full_unstemmed | Model-based gene set analysis for Bioconductor |
title_short | Model-based gene set analysis for Bioconductor |
title_sort | model-based gene set analysis for bioconductor |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117381/ https://www.ncbi.nlm.nih.gov/pubmed/21561920 http://dx.doi.org/10.1093/bioinformatics/btr296 |
work_keys_str_mv | AT bauersebastian modelbasedgenesetanalysisforbioconductor AT robinsonpetern modelbasedgenesetanalysisforbioconductor AT gagneurjulien modelbasedgenesetanalysisforbioconductor |