A flexible R package for nonnegative matrix factorization

Hdl Handle:
http://hdl.handle.net/10147/218132
Title:
A flexible R package for nonnegative matrix factorization
Authors:
Gaujoux, Renaud; Seoighe, Cathal
Citation:
BMC Bioinformatics. 2010 Jul 02;11(1):367
Issue Date:
2-Jul-2010
URI:
http://dx.doi.org/10.1186/1471-2105-11-367; http://hdl.handle.net/10147/218132
Abstract:
Abstract Background Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community. Results Our objective is to provide the bioinformatics community with an open-source, easy-to-use and unified interface to standard NMF algorithms, as well as with a simple framework to help implement and test new NMF methods. For that purpose, we have developed a package for the R/BioConductor platform. The package ports public code to R, and is structured to enable users to easily modify and/or add algorithms. It includes a number of published NMF algorithms and initialization methods and facilitates the combination of these to produce new NMF strategies. Commonly used benchmark data and visualization methods are provided to help in the comparison and interpretation of the results. Conclusions The NMF package helps realize the potential of Nonnegative Matrix Factorization, especially in bioinformatics, providing easy access to methods that have already yielded new insights in many applications. Documentation, source code and sample data are available from CRAN.
Item Type:
Journal Article

Full metadata record

DC FieldValue Language
dc.contributor.authorGaujoux, Renaud-
dc.contributor.authorSeoighe, Cathal-
dc.date.accessioned2012-04-11T10:25:15Z-
dc.date.available2012-04-11T10:25:15Z-
dc.date.issued2010-07-02-
dc.identifier.citationBMC Bioinformatics. 2010 Jul 02;11(1):367-
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2105-11-367-
dc.identifier.urihttp://hdl.handle.net/10147/218132-
dc.description.abstractAbstract Background Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community. Results Our objective is to provide the bioinformatics community with an open-source, easy-to-use and unified interface to standard NMF algorithms, as well as with a simple framework to help implement and test new NMF methods. For that purpose, we have developed a package for the R/BioConductor platform. The package ports public code to R, and is structured to enable users to easily modify and/or add algorithms. It includes a number of published NMF algorithms and initialization methods and facilitates the combination of these to produce new NMF strategies. Commonly used benchmark data and visualization methods are provided to help in the comparison and interpretation of the results. Conclusions The NMF package helps realize the potential of Nonnegative Matrix Factorization, especially in bioinformatics, providing easy access to methods that have already yielded new insights in many applications. Documentation, source code and sample data are available from CRAN.-
dc.titleA flexible R package for nonnegative matrix factorization-
dc.typeJournal Article-
dc.language.rfc3066en-
dc.rights.holderGaujoux et al.; licensee BioMed Central Ltd.-
dc.description.statusPeer Reviewed-
dc.date.updated2012-04-10T15:02:22Z-
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