ORdensity: user-friendly R package to identify differentially expressed genes

Martínez Otzeta, José María; Irigoyen Garbizu, Itziar; Sierra Araujo, Basilio; Arenas Solá, Concepción

dc.contributor.author	Martínez Otzeta, José María
dc.contributor.author	Irigoyen Garbizu, Itziar
dc.contributor.author	Sierra Araujo, Basilio
dc.contributor.author	Arenas Solá, Concepción
dc.date.accessioned	2020-05-13T21:01:26Z
dc.date.available	2020-05-13T21:01:26Z
dc.date.issued	2020-04-07
dc.identifier.citation	BCM Bioinformatics 21(1) : (2020) // Article ID 135	es_ES
dc.identifier.issn	1471-2105
dc.identifier.uri	http://hdl.handle.net/10810/43213
dc.description.abstract	Background Microarray technology provides the expression level of many genes. Nowadays, an important issue is to select a small number of informative differentially expressed genes that provide biological knowledge and may be key elements for a disease. With the increasing volume of data generated by modern biomedical studies, software is required for effective identification of differentially expressed genes. Here, we describe an R package, called ORdensity, that implements a recent methodology (Irigoien and Arenas, 2018) developed in order to identify differentially expressed genes. The benefits of parallel implementation are discussed. Results ORdensity gives the user the list of genes identified as differentially expressed genes in an easy and comprehensible way. The experimentation carried out in an off-the-self computer with the parallel execution enabled shows an improvement in run-time. This implementation may also lead to an important use of memory load. Results previously obtained with simulated and real data indicated that the procedure implemented in the package is robust and suitable for differentially expressed genes identification. Conclusions The new package, ORdensity, offers a friendly and easy way to identify differentially expressed genes, which is very useful for users not familiar with programming. Availability https://github.com/rsait/ORdensity	es_ES
dc.description.sponsorship	The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. This study was partially supported: II by the Spanish Ministerio de Economia y Competitividad (TIN2015-64395-R; PROSA-MED: TIN2016-77820-C3-1-R) and by the Basque Government Research Team Grant (IT313-10) SAIOTEK ProjectSA-2013/00397 and by the University of the Basque Country UPV/EHU (Grant UFI11/45 (BAILab). CA by the Spanish Ministerio de Economia y Competitividad (RTI2018-093337-B-I00), by the Spanish Ministerio de Economia y Competitividad((RTI2018-100968-B-I00) and by Grant 2017SGR622 (GRBIO) from the Departament d'Economia i Coneixement de la Generalitat de Catalunya. The funders had no role in the study design, data collection and interpretation, or the decision to submit the work for publication.	es_ES
dc.language.iso	eng	es_ES
dc.publisher	BCM	es_ES
dc.relation	info:eu-repo/grantAgreement/MINECO/RTI2018-100968-B-I00	es_ES
dc.relation	info:eu-repo/grantAgreement/MINECO/TIN2015-64395-R PROSA-MED	es_ES
dc.relation	info:eu-repo/grantAgreement/MINECO/TIN2016-77820-C3-1-R	es_ES
dc.relation	info:eu-repo/grantAgreement/MINECO/RTI2018-093337-B-I00	es_ES
dc.rights	info:eu-repo/semantics/openAccess	es_ES
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/es/	*
dc.subject	differentially expressed gene	es_ES
dc.subject	multivariate statistics	es_ES
dc.subject	outlier	es_ES
dc.subject	parallel implementation	es_ES
dc.subject	quantile	es_ES
dc.subject	R package	es_ES
dc.title	ORdensity: user-friendly R package to identify differentially expressed genes	es_ES
dc.type	info:eu-repo/semantics/article	es_ES
dc.rights.holder	This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.	es_ES
dc.rights.holder	Atribución 3.0 España	*
dc.relation.publisherversion	https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3463-4	es_ES
dc.identifier.doi	10.1186/s12859-020-3463-4
dc.departamentoes	Ciencia de la computación e inteligencia artificial	es_ES
dc.departamentoeu	Konputazio zientziak eta adimen artifiziala	es_ES

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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Except where otherwise noted, this item's license is described as This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.