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Identification of genetic variants associated with alternative splicing using sQTLseekeR

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dc.contributor.author Monlong, Jean
dc.contributor.author Calvo, Miquel
dc.contributor.author Ferreira, Pedro G.
dc.contributor.author Guigó Serra, Roderic
dc.date.accessioned 2015-06-16T08:18:37Z
dc.date.available 2015-06-16T08:18:37Z
dc.date.issued 2014
dc.identifier.citation Monlong J, Calvo M, Ferreira PG, Guigó R. Identification of genetic variants associated with alternative splicing using sQTLseekeR. Nature Communications. 2014;5:4698. DOI 10.1038/ncomms5698
dc.identifier.issn 2041-1723
dc.identifier.uri http://hdl.handle.net/10230/23832
dc.description.abstract Identification of genetic variants affecting splicing in RNA sequencing population studies is still in its infancy. Splicing phenotype is more complex than gene expression and ought to be treated as a multivariate phenotype to be recapitulated completely. Here we represent the splicing pattern of a gene as the distribution of the relative abundances of a gene’s alternative transcript isoforms. We develop a statistical framework that uses a distance-based approach to compute the variability of splicing ratios across observations, and a non-parametric analogue to multivariate analysis of variance. We implement this approach in the R package sQTLseekeR and use it to analyze RNA-Seq data from the Geuvadis project in 465 individuals. We identify hundreds of single nucleotide polymorphisms (SNPs) as splicing QTLs (sQTLs), including some falling in genome-wide association study SNPs. By developing the appropriate metrics, we show that sQTLseekeR compares favorably with existing methods that rely on univariate approaches, predicting variants that behave as expected from mutations affecting splicing.
dc.description.sponsorship This work was supported by grant 1R01MH090941-01 and R01MH101814 from the US National Institutes of Health, and grants BIO2011-26205 and CSD2007-00050 from the Ministerio de Educación y Ciencia (Spain) and grant ERC_294653 from the European Research Council.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Publishing Group
dc.relation.ispartof Nature Communications. 2014;5:4698
dc.rights © Nature Publishing Group. http://dx.doi.org/10.1038/ncomms5698/nThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.other RNA
dc.subject.other Biologia molecular
dc.subject.other Genomes
dc.title Identification of genetic variants associated with alternative splicing using sQTLseekeR
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/ncomms5698
dc.subject.keyword Biological sciences
dc.subject.keyword Bioinformatics
dc.subject.keyword Genetics
dc.relation.projectID info:eu-repo/grantAgreement/EC/ERC/294653
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BIO2011-26205
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/CSD2007-00050
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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