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Pergola: boosting visualization and analysis of longitudinal data by unlocking genomic analysis tools

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dc.contributor.author Espinosa-Carrasco, José
dc.contributor.author Erb, Ionas
dc.contributor.author Hermoso Pulido, Antonio
dc.contributor.author Ponomarenko, Julia
dc.contributor.author Dierssen, Mara
dc.contributor.author Notredame, Cedric
dc.date.accessioned 2019-11-21T12:50:31Z
dc.date.available 2019-11-21T12:50:31Z
dc.date.issued 2018
dc.identifier.citation Espinosa-Carrasco J, Erb I, Hermoso Pulido T, Ponomarenko J, Dierssen M, Notredame C. Pergola: boosting visualization and analysis of longitudinal data by unlocking genomic analysis tools. iScience. 2018; 9:244-257. DOI 10.1016/j.isci.2018.10.023
dc.identifier.issn 2589-0042
dc.identifier.uri http://hdl.handle.net/10230/42918
dc.description.abstract The growing appetite of behavioral neuroscience for automated data production is prompting the need for new computational standards allowing improved interoperability, reproducibility, and shareability. We show here how these issues can be solved by repurposing existing genomic formats whose structure perfectly supports the handling of time series. This allows existing genomic analysis and visualization tools to be deployed onto behavioral data. As a proof of principle, we implemented the conversion procedure in Pergola, an open source software, and used genomics tools to reproduce results obtained in mouse, fly, and worm. We also show how common genomics techniques such as principal component analysis, hidden Markov modeling, and volcano plots can be deployed on the reformatted behavioral data. These analyses are easy to share because they depend on the scripting of public software. They are also easy to reproduce thanks to their integration within Nextflow, a workflow manager using containerized software.
dc.description.sponsorship We acknowledge the support of the “Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat i del Fons Social Europeu,” Spanish Ministry of Economy, Industry and Competitiveness (MEIC) under grant numbers BFU2014-55062-P and BFU2017-88264-P, the EMBL partnership, FEDER, the “Centro de Excelencia Severo Ochoa” Programme, and the CERCA Programme/Generalitat de Catalunya. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 635290-PanCanRisk and OpenRiskNet_731076. This reflects only the author's view and the funder is not responsible for any use that may be made of the information it contains. M.D. is supported by DIUE de la Generalitat de Catalunya (Grups consolidats SGR 2017/926), the Fondation Jérôme Lejeune (Paris, France), MINECO (SAF2013-49129-C2-1-R; SAF2016-79956-R), CDTI (“Smartfoods”) and EU (EraNet Neuron PCIN-2013-060 and JPND AC17/00006), and the Catalan foundation “La Marató de TV3” (#2016/20-30). The CIBER of Rare Diseases is an initiative of the ISCIII.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof iScience. 2018; 9:244-257
dc.rights © 2018 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.title Pergola: boosting visualization and analysis of longitudinal data by unlocking genomic analysis tools
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.isci.2018.10.023
dc.subject.keyword Behavioral neuroscience
dc.subject.keyword Bioinformatics
dc.subject.keyword Biological sciences
dc.subject.keyword Genetics
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/BFU2014-55062
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BFU2017-88264-P
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/635290
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/SAF2013-49129-C2-1-R
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/SAF2016-79956-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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