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dc.contributor.authorMartí-Gómez, Carlos 
dc.contributor.authorLara-Pezzi, Enrique 
dc.contributor.authorSanchez-Cabo, Fatima 
dc.date.accessioned2020-04-20T12:52:57Z
dc.date.available2020-04-20T12:52:57Z
dc.date.issued2020-04-01
dc.identifier.citationBioinformatics. 2020; 36(7):2134-2141es_ES
dc.identifier.issn1367-4803es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/9628
dc.description.abstractMOTIVATION: Alternative splicing (AS) is an important mechanism in the generation of transcript diversity across mammals. AS patterns are dynamically regulated during development and in response to environmental changes. Defects or perturbations in its regulation may lead to cancer or neurological disorders, among other pathological conditions. The regulatory mechanisms controlling AS in a given biological context are typically inferred using a two-step framework: differential AS analysis followed by enrichment methods. These strategies require setting rather arbitrary thresholds and are prone to error propagation along the analysis. RESULTS: To overcome these limitations, we propose dSreg, a Bayesian model that integrates RNA-seq with data from regulatory features, e.g. binding sites of RNA-binding proteins. dSreg identifies the key underlying regulators controlling AS changes and quantifies their activity while simultaneously estimating the changes in exon inclusion rates. dSreg increased both the sensitivity and the specificity of the identified AS changes in simulated data, even at low read coverage. dSreg also showed improved performance when analyzing a collection of knock-down RNA-binding proteins' experiments from ENCODE, as opposed to traditional enrichment methods, such as over-representation analysis and gene set enrichment analysis. dSreg opens the possibility to integrate a large amount of readily available RNA-seq datasets at low coverage for AS analysis and allows more cost-effective RNA-seq experiments. AVAILABILITY AND IMPLEMENTATION: dSreg was implemented in python using stan and is freely available to the community at https://bitbucket.org/cmartiga/dsreg. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.es_ES
dc.description.sponsorshipThis work was supported by grants from the European Union [CardioNeTITN-289600, CardioNext-608027]; the Spanish Ministry of Economy and Competitiveness [SAF2015-65722-R, SAF2012-31451]; the Instituto de salud Carlos III (ISCIII) [CPII14/00027, RD012/0042/0066]; the Madrid Regional Government [2010-BMD-2321 “Fibroteam”]. The study also received support from the Plan Estatal de I+D+I 2013-2016 – European Regional Development Fund (ERDF) “A way of making Europe”, Spain. The CNIC is supported by the Spanish Ministry of Economy, Industry and Competitiveness and the Pro-CNIC Foundation and is a Severo Ochoa Center of Excellence (MEIC award SEV-2015-0505).es_ES
dc.language.isoenges_ES
dc.publisherOxford Academicses_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titledSreg: a Bayesian model to integrate changes in splicing and RNA-binding protein activityes_ES
dc.typeArtículoes_ES
dc.rights.licenseAtribución 4.0 Internacional*
dc.identifier.pubmedID31834368es_ES
dc.format.volume36es_ES
dc.format.number7es_ES
dc.format.page2134-2141es_ES
dc.identifier.doi10.1093/bioinformatics/btz915es_ES
dc.contributor.funderEuropean Commissiones_ES
dc.contributor.funderMinisterio de Economía, Industria y Competitividad (España)es_ES
dc.contributor.funderInstituto de Salud Carlos III - ISCIIIes_ES
dc.contributor.funderComunidad de Madrides_ES
dc.contributor.funderEuropean Regional Development Fund (ERDF/FEDER)es_ES
dc.contributor.funderFundación ProCNICes_ES
dc.description.peerreviewedes_ES
dc.identifier.e-issn1367-4811es_ES
dc.relation.publisherversionhttps://doi.org/10.1093/bioinformatics/btz915es_ES
dc.identifier.journalBioinformatics (Oxford, England)es_ES
dc.repisalud.orgCNICCNIC::Grupos de investigación::Regulación Molecular de la Insuficiencia Cardiacaes_ES
dc.repisalud.orgCNICCNIC::Unidades técnicas::Bioinformáticaes_ES
dc.repisalud.institucionCNICes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SEV-2015-0505es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SAF2015-65722-Res_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SAF2012-31451es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/CPII14/00027es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/RD012/0042/0066es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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