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Next maSigPro: updating maSigPro Bioconductor package for RNA-seq time series

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Next maSigPro: updating maSigPro Bioconductor package for RNA-seq time series

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dc.contributor.author Nueda, María José es_ES
dc.contributor.author Tarazona Campos, Sonia es_ES
dc.contributor.author Conesa, Ana es_ES
dc.date.accessioned 2016-05-02T12:49:37Z
dc.date.available 2016-05-02T12:49:37Z
dc.date.issued 2014-09-15
dc.identifier.issn 1367-4803
dc.identifier.uri http://hdl.handle.net/10251/63346
dc.description.abstract [EN] Motivation: The widespread adoption of RNA-seq to quantitatively measure gene expression has increased the scope of sequencing experimental designs to include time-course experiments. maSigPro is an R package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data. Results: We have updated maSigPro to support RNA-seq time series analysis by introducing generalized linear models in the algorithm to support the modeling of count data while maintaining the traditional functionalities of the package. We show a good performance of the maSigPro-GLM method in several simulated time-course scenarios and in a real experimental dataset. Availability and implementation: The package is freely available under the LGPL license from the Bioconductor Web site (http:// bioconductor.org) es_ES
dc.description.sponsorship This work has been funded by the FP7 STATegra [GA-30600] project, EU FP7 [30600] and the Spanish MINECO [BIO2012-40244]. en_EN
dc.language Inglés es_ES
dc.publisher Oxford University Press (OUP): Policy B - Oxford Open Option B es_ES
dc.relation.ispartof Bioinformatics es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Differential expression analysis es_ES
dc.subject Gene es_ES
dc.subject Depth es_ES
dc.subject Course microarray experiments es_ES
dc.subject Normalization es_ES
dc.subject Sequence es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Next maSigPro: updating maSigPro Bioconductor package for RNA-seq time series es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1093/bioinformatics/btu333
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BIO2012-40244/ES/DESARROLLO DE RECURSOS COMPUTACIONALES PARA LA CARACTERIZACION Y ANOTACION FUNCIONAL DE ARN NO CODIFICANTE./ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/30600/EU/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Nueda, MJ.; Tarazona Campos, S.; Conesa, A. (2014). Next maSigPro: updating maSigPro Bioconductor package for RNA-seq time series. Bioinformatics. 30(18):2598-2602. https://doi.org/10.1093/bioinformatics/btu333 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://dx.doi.org/10.1093/bioinformatics/btu333 es_ES
dc.description.upvformatpinicio 2598 es_ES
dc.description.upvformatpfin 2602 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 30 es_ES
dc.description.issue 18 es_ES
dc.relation.senia 269164 es_ES
dc.identifier.eissn 1460-2059
dc.identifier.pmid 24894503 en_EN
dc.identifier.pmcid PMC4155246 en_EN
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Economía y Competitividad
dc.description.references Anders, S., & Huber, W. (2010). Differential expression analysis for sequence count data. Genome Biology, 11(10). doi:10.1186/gb-2010-11-10-r106 es_ES
dc.description.references Bullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010). Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics, 11(1). doi:10.1186/1471-2105-11-94 es_ES
dc.description.references Conesa, A., Nueda, M. J., Ferrer, A., & Talon, M. (2006). maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics, 22(9), 1096-1102. doi:10.1093/bioinformatics/btl056 es_ES
dc.description.references Hacquard, S., Kracher, B., Maekawa, T., Vernaldi, S., Schulze-Lefert, P., & Ver Loren van Themaat, E. (2013). Mosaic genome structure of the barley powdery mildew pathogen and conservation of transcriptional programs in divergent hosts. Proceedings of the National Academy of Sciences, 110(24), E2219-E2228. doi:10.1073/pnas.1306807110 es_ES
dc.description.references Hoogerwerf, W. A., Sinha, M., Conesa, A., Luxon, B. A., Shahinian, V. B., Cornélissen, G., … Cassone, V. M. (2008). Transcriptional Profiling of mRNA Expression in the Mouse Distal Colon. Gastroenterology, 135(6), 2019-2029. doi:10.1053/j.gastro.2008.08.048 es_ES
dc.description.references Levin, A. M., de Vries, R. P., Conesa, A., de Bekker, C., Talon, M., Menke, H. H., … Wösten, H. A. B. (2007). Spatial Differentiation in the Vegetative Mycelium ofAspergillus niger. Eukaryotic Cell, 6(12), 2311-2322. doi:10.1128/ec.00244-07 es_ES
dc.description.references Liu, Y., Zhou, J., & White, K. P. (2013). RNA-seq differential expression studies: more sequence or more replication? Bioinformatics, 30(3), 301-304. doi:10.1093/bioinformatics/btt688 es_ES
dc.description.references Maekawa, T., Kracher, B., Vernaldi, S., Ver Loren van Themaat, E., & Schulze-Lefert, P. (2012). Conservation of NLR-triggered immunity across plant lineages. Proceedings of the National Academy of Sciences, 109(49), 20119-20123. doi:10.1073/pnas.1218059109 es_ES
dc.description.references Medina, I., Carbonell, J., Pulido, L., Madeira, S. C., Goetz, S., Conesa, A., … Dopazo, J. (2010). Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Nucleic Acids Research, 38(suppl_2), W210-W213. doi:10.1093/nar/gkq388 es_ES
dc.description.references Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008). Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods, 5(7), 621-628. doi:10.1038/nmeth.1226 es_ES
dc.description.references Nueda, M. j., Ferrer, A., & Conesa, A. (2011). ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Biostatistics, 13(3), 553-566. doi:10.1093/biostatistics/kxr042 es_ES
dc.description.references Risso, D., Schwartz, K., Sherlock, G., & Dudoit, S. (2011). GC-Content Normalization for RNA-Seq Data. BMC Bioinformatics, 12(1), 480. doi:10.1186/1471-2105-12-480 es_ES
dc.description.references Roberts, A., & Pachter, L. (2012). Streaming fragment assignment for real-time analysis of sequencing experiments. Nature Methods, 10(1), 71-73. doi:10.1038/nmeth.2251 es_ES
dc.description.references Robinson, M. D., & Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology, 11(3), R25. doi:10.1186/gb-2010-11-3-r25 es_ES
dc.description.references Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2009). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26(1), 139-140. doi:10.1093/bioinformatics/btp616 es_ES
dc.description.references Sims, D., Sudbery, I., Ilott, N. E., Heger, A., & Ponting, C. P. (2014). Sequencing depth and coverage: key considerations in genomic analyses. Nature Reviews Genetics, 15(2), 121-132. doi:10.1038/nrg3642 es_ES
dc.description.references Tarazona, S., Garcia-Alcalde, F., Dopazo, J., Ferrer, A., & Conesa, A. (2011). Differential expression in RNA-seq: A matter of depth. Genome Research, 21(12), 2213-2223. doi:10.1101/gr.124321.111 es_ES
dc.description.references Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., … Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protocols, 7(3), 562-578. doi:10.1038/nprot.2012.016 es_ES
dc.description.references Terol, J., Conesa, A., Colmenero, J. M., Cercos, M., Tadeo, F., Agustí, J., … Talon, M. (2007). BMC Genomics, 8(1), 31. doi:10.1186/1471-2164-8-31 es_ES


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