A flexible R package for nonnegative matrix factorization

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dc.contributor.authorGaujoux, Renauden_ZA
dc.contributor.authorSeoighe, Cathalen_ZA
dc.date.accessioned2015-11-11T11:57:28Z
dc.date.available2015-11-11T11:57:28Z
dc.date.issued2010en_ZA
dc.description.abstractBACKGROUND: 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.en_ZA
dc.identifier.apacitationGaujoux, R., & Seoighe, C. (2010). A flexible R package for nonnegative matrix factorization. <i>BMC Bioinformatics</i>, http://hdl.handle.net/11427/14879en_ZA
dc.identifier.chicagocitationGaujoux, Renaud, and Cathal Seoighe "A flexible R package for nonnegative matrix factorization." <i>BMC Bioinformatics</i> (2010) http://hdl.handle.net/11427/14879en_ZA
dc.identifier.citationGaujoux, R., & Seoighe, C. (2010). A flexible R package for nonnegative matrix factorization. BMC bioinformatics, 11(1), 367.en_ZA
dc.identifier.ris TY - Journal Article AU - Gaujoux, Renaud AU - Seoighe, Cathal AB - 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. DA - 2010 DB - OpenUCT DO - 10.1186/1471-2105-11-367 DP - University of Cape Town J1 - BMC Bioinformatics LK - https://open.uct.ac.za PB - University of Cape Town PY - 2010 T1 - A flexible R package for nonnegative matrix factorization TI - A flexible R package for nonnegative matrix factorization UR - http://hdl.handle.net/11427/14879 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/14879
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2105-11-367
dc.identifier.vancouvercitationGaujoux R, Seoighe C. A flexible R package for nonnegative matrix factorization. BMC Bioinformatics. 2010; http://hdl.handle.net/11427/14879.en_ZA
dc.language.isoengen_ZA
dc.publisherBioMed Central Ltden_ZA
dc.publisher.departmentInstitute of Infectious Disease and Molecular Medicineen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Licenseen_ZA
dc.rights.holder2010 Gaujoux and Seoighe; licensee BioMed Central Ltd.en_ZA
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_ZA
dc.sourceBMC Bioinformaticsen_ZA
dc.source.urihttp://www.biomedcentral.com/bmcbioinformatics/en_ZA
dc.subject.otherBioinformaticsen_ZA
dc.titleA flexible R package for nonnegative matrix factorizationen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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