Please use this identifier to cite or link to this item: http://hdl.handle.net/10668/10698
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dc.contributor.authorMuchmore, B
dc.contributor.authorAlarcón-Riquelme, M E
dc.date.accessioned2023-01-25T09:42:41Z-
dc.date.available2023-01-25T09:42:41Z-
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10668/10698-
dc.description.abstractHere we present open-source software for the analysis of high-dimensional cytometry data using state of the art algorithms. Importantly, use of the software requires no programming ability, and output files can either be interrogated directly in CymeR or they can be used downstream with any other cytometric data analysis platform. Also, because we use Docker to integrate the multitude of components that form the basis of CymeR, we have additionally developed a proof-of-concept of how future open-source bioinformatic programs with graphical user interfaces could be developed. CymeR is open-source software that ties several components into a single program that is perhaps best thought of as a self-contained data analysis operating system. Please see https://github.com/bmuchmore/CymeR/wiki for detailed installation instructions. brian.muchmore@genyo.es or marta.alarcon@genyo.es.
dc.language.isoen
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject.meshAlgorithms
dc.subject.meshComputational Biology
dc.subject.meshFlow Cytometry
dc.subject.meshSoftware
dc.titleCymeR: cytometry analysis using KNIME, docker and R.
dc.typeresearch article
dc.identifier.pmid27998935
dc.rights.accessRightsopen access
dc.identifier.doi10.1093/bioinformatics/btw707
dc.identifier.essn1367-4811
dc.identifier.pmcPMC5870801
dc.identifier.unpaywallURLhttps://academic.oup.com/bioinformatics/article-pdf/33/5/776/25148390/btw707.pdf
dc.issue.number5
dc.journal.titleBioinformatics (Oxford, England)
dc.journal.titleabbreviationBioinformatics
dc.organizationCentro Pfizer-Universidad de Granada-Junta de Andalucía de Genómica e Investigación Oncológica-GENYO
dc.page.number776-778
dc.pubmedtypeJournal Article
dc.volume.number33
dc.type.hasVersionVoR
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870801/pdf
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