{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T21:41:13Z","timestamp":1722721273464},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,28]],"date-time":"2016-10-28T00:00:00Z","timestamp":1477612800000},"content-version":"vor","delay-in-days":139,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Alternative splicing is an important mechanism in which the regions of pre-mRNAs are differentially joined in order to form different transcript isoforms. Alternative splicing is involved in the regulation of normal physiological functions but also linked to the development of diseases such as cancer. We analyse differential expression and splicing using RNA-sequencing time series in three different settings: overall gene expression levels, absolute transcript expression levels and relative transcript expression levels.<\/jats:p>\n               <jats:p>Results: Using estrogen receptor \u03b1 signaling response as a model system, our Gaussian process-based test identifies genes with differential splicing and\/or differentially expressed transcripts. We discover genes with consistent changes in alternative splicing independent of changes in absolute expression and genes where some transcripts change whereas others stay constant in absolute level. The results suggest classes of genes with different modes of alternative splicing regulation during the experiment.<\/jats:p>\n               <jats:p>Availability and Implementation: R and Matlab codes implementing the method are available at https:\/\/github.com\/PROBIC\/diffsplicing . An interactive browser for viewing all model fits is available at http:\/\/users.ics.aalto.fi\/hande\/splicingGP\/<\/jats:p>\n               <jats:p>Contact: \u00a0hande.topa@helsinki.fi or antti.honkela@helsinki.fi<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw283","type":"journal-article","created":{"date-parts":[[2016,6,15]],"date-time":"2016-06-15T15:43:52Z","timestamp":1466005432000},"page":"i147-i155","source":"Crossref","is-referenced-by-count":9,"title":["Analysis of differential splicing suggests different modes of short-term splicing regulation"],"prefix":"10.1093","volume":"32","author":[{"given":"Hande","family":"Topa","sequence":"first","affiliation":[{"name":"1 Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Espoo 00076, Finland"},{"name":"2 Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki 00014, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antti","family":"Honkela","sequence":"additional","affiliation":[{"name":"2 Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki 00014, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,6,11]]},"reference":[{"key":"2023020112323188100_btw283-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":"2023020112323188100_btw283-B2","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1007\/s11004-005-7383-7","article-title":"Compositional data analysis: where are we and where should we be heading?","volume":"37","author":"Aitchison","year":"2005","journal-title":"Math. 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