{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T06:10:44Z","timestamp":1770358244693,"version":"3.49.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"19","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Isoform quantification is an important goal of RNA-seq experiments, yet it remains problematic for genes with low expression or several isoforms. These difficulties may in principle be ameliorated by exploiting correlated experimental designs, such as time series or dosage response experiments. Time series RNA-seq experiments, in particular, are becoming increasingly popular, yet there are no methods that explicitly leverage the experimental design to improve isoform quantification.<\/jats:p>\n               <jats:p>Results: Here, we present DICEseq, the first isoform quantification method tailored to correlated RNA-seq experiments. DICEseq explicitly models the correlations between different RNA-seq experiments to aid the quantification of isoforms across experiments. Numerical experiments on simulated datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. On real datasets, our results show that DICEseq provides substantially more reproducible and robust quantifications, increasing the correlation of estimates from replicate datasets by up to 10% on genes with low or moderate expression levels (bottom third of all genes). Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Our results have strong implications for the design of RNA-seq experiments, and offer a novel tool for improved analysis of such datasets.<\/jats:p>\n               <jats:p>Availability and Implementation: Python code is freely available at http:\/\/diceseq.sf.net.<\/jats:p>\n               <jats:p>Contact: \u00a0G.Sanguinetti@ed.ac.uk<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw364","type":"journal-article","created":{"date-parts":[[2016,6,19]],"date-time":"2016-06-19T00:18:20Z","timestamp":1466295500000},"page":"2965-2972","source":"Crossref","is-referenced-by-count":15,"title":["Statistical modeling of isoform splicing dynamics from RNA-seq time series data"],"prefix":"10.1093","volume":"32","author":[{"given":"Yuanhua","family":"Huang","sequence":"first","affiliation":[{"name":"1 School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK"}]},{"given":"Guido","family":"Sanguinetti","sequence":"additional","affiliation":[{"name":"1 School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK"},{"name":"2 Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Edinburgh EH9 3BF, UK"}]}],"member":"286","published-online":{"date-parts":[[2016,6,17]]},"reference":[{"key":"2023020113451337000_btw364-B1","doi-asserted-by":"crossref","first-page":"i113","DOI":"10.1093\/bioinformatics\/btu274","article-title":"Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation","volume":"30","author":"\u00c4ij\u00f6","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020113451337000_btw364-B2","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1038\/nrg3244","article-title":"Studying and modelling dynamic biological processes using time-series gene expression data","volume":"13","author":"Bar-Joseph","year":"2012","journal-title":"Nat. Rev. Genet"},{"key":"2023020113451337000_btw364-B3","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s13059-015-0848-1","article-title":"Transcriptome-wide RNA processing kinetics revealed using extremely short 4tU labeling","volume":"16","author":"Barrass","year":"2015","journal-title":"Genome Biol"},{"key":"2023020113451337000_btw364-B4","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.cell.2006.06.023","article-title":"Alternative splicing: new insights from global analyses","volume":"126","author":"Blencowe","year":"2006","journal-title":"Cell"},{"key":"2023020113451337000_btw364-B5","doi-asserted-by":"crossref","first-page":"2829","DOI":"10.1093\/bioinformatics\/btv288","article-title":"INSPEcT: a Computational Tool to Infer mRNA Synthesis, Processing and Degradation Dynamics from RNA-and 4sU-seq Time Course Experiments","volume":"31","author":"de Pretis","year":"2015","journal-title":"Bioinformatics"},{"key":"2023020113451337000_btw364-B6","doi-asserted-by":"crossref","first-page":"e0121945.","DOI":"10.1371\/journal.pone.0121945","article-title":"Cocor: a comprehensive solution for the statistical comparison of correlations","volume":"10","author":"Diedenhofen","year":"2015","journal-title":"PloS One"},{"key":"2023020113451337000_btw364-B7","doi-asserted-by":"crossref","first-page":"857","DOI":"10.15252\/msb.20156526","article-title":"Determinants of RNA metabolism in the Schizosaccharomyces pombe genome","volume":"12","author":"Eser","year":"2016","journal-title":"Mol. Syst. Biol"},{"key":"2023020113451337000_btw364-B8","doi-asserted-by":"crossref","first-page":"R69.","DOI":"10.1186\/gb-2014-15-5-r69","article-title":"4sUDRB-seq: measuring genomewide transcriptional elongation rates and initiation frequencies within cells","volume":"15","author":"Fuchs","year":"2014","journal-title":"Genome Biol"},{"key":"2023020113451337000_btw364-B9","doi-asserted-by":"crossref","DOI":"10.21034\/sr.148","volume-title":"Evaluating the Accuracy of sampling-Based Approaches to the Calculation of Posterior Moments","author":"Geweke","year":"1991"},{"key":"2023020113451337000_btw364-B10","doi-asserted-by":"crossref","first-page":"1721","DOI":"10.1093\/bioinformatics\/bts260","article-title":"Identifying differentially expressed transcripts from RNA-seq data with biological variation","volume":"28","author":"Glaus","year":"2012","journal-title":"Bioinformatics"},{"key":"2023020113451337000_btw364-B11","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/S0168-9525(00)02176-4","article-title":"Alternative splicing: increasing diversity in the proteomic world","volume":"17","author":"Graveley","year":"2001","journal-title":"Trends Genet"},{"key":"2023020113451337000_btw364-B12","doi-asserted-by":"crossref","first-page":"13115","DOI":"10.1073\/pnas.1420404112","article-title":"Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays","volume":"112","author":"Honkela","year":"2015","journal-title":"Proc. Natl. Acad. Sci. U. S. A"},{"key":"2023020113451337000_btw364-B13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-015-0702-5","article-title":"Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data","volume":"16","author":"Kanitz","year":"2015","journal-title":"Genome Biol"},{"key":"2023020113451337000_btw364-B14","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1038\/nmeth.1528","article-title":"Analysis and design of RNA sequencing experiments for identifying isoform regulation","volume":"7","author":"Katz","year":"2010","journal-title":"Nat. Methods"},{"key":"2023020113451337000_btw364-B15","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1038\/nmeth.3317","article-title":"HISAT: a fast spliced aligner with low memory requirements","volume":"12","author":"Kim","year":"2015","journal-title":"Nat. Methods"},{"key":"2023020113451337000_btw364-B16","author":"Lawrence","year":"2006"},{"key":"2023020113451337000_btw364-B17","doi-asserted-by":"crossref","first-page":"9.","DOI":"10.1186\/1748-7188-6-9","article-title":"Estimation of alternative splicing isoform frequencies from RNA-Seq data","volume":"6","author":"Nicolae","year":"2011","journal-title":"Algorithms Mol. Biol"},{"key":"2023020113451337000_btw364-B18","volume-title":"Gaussian Processes for Machine Learning","author":"Rasmussen","year":"2006"},{"key":"2023020113451337000_btw364-B19","doi-asserted-by":"crossref","first-page":"R22","DOI":"10.1186\/gb-2011-12-3-r22","article-title":"Improving RNA-Seq expression estimates by correcting for fragment bias","volume":"12","author":"Roberts","year":"2011","journal-title":"Genome Biol"},{"key":"2023020113451337000_btw364-B20","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/nrg.2015.3","article-title":"RNA mis-splicing in disease","volume":"17","author":"Scotti","year":"2016","journal-title":"Nat. Rev. Genet"},{"key":"2023020113451337000_btw364-B21","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1089\/cmb.2009.0175","article-title":"A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series","volume":"17","author":"Stegle","year":"2010","journal-title":"J. Comput. Biol"},{"key":"2023020113451337000_btw364-B22","doi-asserted-by":"crossref","first-page":"320.","DOI":"10.1186\/1471-2105-14-320","article-title":"Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)","volume":"14","author":"Sturgill","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2023020113451337000_btw364-B23","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1038\/nbt.1621","article-title":"Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation","volume":"28","author":"Trapnell","year":"2010","journal-title":"Nat. Biotechnol"},{"key":"2023020113451337000_btw364-B24","doi-asserted-by":"crossref","first-page":"e151","DOI":"10.1182\/blood-2012-01-407528","article-title":"Identification of early gene expression changes during human Th17 cell differentiation","volume":"119","author":"Tuomela","year":"2012","journal-title":"Blood"},{"key":"2023020113451337000_btw364-B25","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1101\/gr.171405.113","article-title":"Rate of elongation by RNA polymerase II is associated with specific gene features and epigenetic modifications","volume":"24","author":"Veloso","year":"2014","journal-title":"Genome Res"},{"key":"2023020113451337000_btw364-B26","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1038\/nature07509","article-title":"Alternative isoform regulation in human tissue transcriptomes","volume":"456","author":"Wang","year":"2008","journal-title":"Nature"},{"key":"2023020113451337000_btw364-B27","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nrg2484","article-title":"RNA-Seq: a revolutionary tool for transcriptomics","volume":"10","author":"Wang","year":"2009","journal-title":"Nat. Rev. Genet"},{"key":"2023020113451337000_btw364-B28","doi-asserted-by":"crossref","first-page":"2031","DOI":"10.1101\/gr.131847.111","article-title":"Ultrashort and progressive 4sU-tagging reveals key characteristics of RNA processing at nucleotide resolution","volume":"22","author":"Windhager","year":"2012","journal-title":"Genome Res"},{"key":"2023020113451337000_btw364-B29","doi-asserted-by":"crossref","first-page":"16219","DOI":"10.1073\/pnas.1408886111","article-title":"A circadian gene expression atlas in mammals: implications for biology and medicine","volume":"111","author":"Zhang","year":"2014","journal-title":"Proc. Natl. Acad. Sci. U. S. A"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/2965\/49021095\/bioinformatics_32_19_2965.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/2965\/49021095\/bioinformatics_32_19_2965.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T23:50:39Z","timestamp":1675295439000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/19\/2965\/2196599"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,17]]},"references-count":29,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2016,10,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw364","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,10,1]]},"published":{"date-parts":[[2016,6,17]]}}}