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dc.contributor.authorBarrachina Mir, Sergio
dc.contributor.authorCastillo Catalán, María Isabel
dc.contributor.authorMartínez Pérez, Héctor
dc.contributor.authorMedina, Ignacio
dc.contributor.authorTárraga, Joaquín
dc.contributor.authorQuintana-Orti, Enrique S.
dc.contributor.authorDopazo, Joaquín
dc.contributor.authorSalavert Torres, José
dc.contributor.authorBlanquer Espert, Ignacio
dc.contributor.authorPaschall, J.
dc.contributor.authorHernández-García, V.
dc.date.accessioned2016-05-24T09:28:06Z
dc.date.available2016-05-24T09:28:06Z
dc.date.issued2016
dc.identifier.citationI. Medina, J. Tárraga, H. Martínez, S. Barrachina, M. I. Castillo, J. Paschall, J. Salavert-Torres, I. Blanquer-Espert, V. Hernández-García, E. S. Quintana-Ortí, and J. Dopazo. Highly sensitive and ultrafast read mapping for RNA-seq analysis DNA Res first published online January 5, 2016 doi:10.1093/dnares/dsv039ca_CA
dc.identifier.issn1340-2838
dc.identifier.issn1756-1663
dc.identifier.urihttp://hdl.handle.net/10234/159928
dc.description.abstractAs sequencing technologies progress, the amount of data produced grows exponentially, shifting the bottleneck of discovery towards the data analysis phase. In particular, currently available mapping solutions for RNA-seq leave room for improvement in terms of sensitivity and performance, hindering an efficient analysis of transcriptomes by massive sequencing. Here, we present an innovative approach that combines re-engineering, optimization and parallelization. This solution results in a significant increase of mapping sensitivity over a wide range of read lengths and substantial shorter runtimes when compared with current RNA-seq mapping methods available.ca_CA
dc.description.sponsorShipThis work is supported by grants from the Spanish Ministry of Economy and Competitiveness (BIO2014-57291-R) and co-funded with European Regional Development Funds (ERDF), AECID (D/016099/08) and from the Conselleria d’Educacio of the Valencian Community (PROMETEOII/2014/025). This work has been carried out in the context of the HPC4G initiative (http://www.hpc4g.org) and the Bull-CIPF Chair for Computational Genomics. Funding to pay the Open Access publication charges for this article was provided by grant BIO2014-57291-R from the Spanish Ministry of Economy and Competitiveness (MINECO), co-funded with European Regional Development Funds (ERDF).ca_CA
dc.format.extent8 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherOxford University Pressca_CA
dc.rightsAttribution-NonCommercial 4.0 Spain*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectRNA-seqca_CA
dc.subjectmappingca_CA
dc.subjectBurrows-Wheeler Transformca_CA
dc.subjecthigh-performance computingca_CA
dc.titleHighly sensitive and ultrafast read mapping for RNA-seq analysisca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1093/dnares/dsv039
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://dnaresearch.oxfordjournals.org/content/early/2016/01/05/dnares.dsv039.full.pdf+htmlca_CA


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