{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:45:30Z","timestamp":1740185130282,"version":"3.37.3"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2018,2,21]],"date-time":"2018-02-21T00:00:00Z","timestamp":1519171200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM108600","R01HL113147","R01HL113147"],"award-info":[{"award-number":["R01GM108600","R01HL113147","R01HL113147"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Alternative splicing and alternative transcription are a major mechanism for generating transcriptome diversity. Differential alternative splicing and transcription (DAST), which describe different usage of transcript isoforms across different conditions, can complement differential expression in characterizing gene regulation. However, the analysis of DAST is challenging because only a small fraction of RNA-seq reads is informative for isoforms. Several methods have been developed to detect exon-based and gene-based DAST, but they suffer from power loss for genes with many isoforms.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We present PennDiff, a novel statistical method that makes use of information on gene structures and pre-estimated isoform relative abundances, to detect DAST from RNA-seq data. PennDiff has several advantages. First, grouping exons avoids multiple testing for \u2018exons\u2019 originated from the same isoform(s). Second, it utilizes all available reads in exon-inclusion level estimation, which is different from methods that only use junction reads. Third, collapsing isoforms sharing the same alternative exons reduces the impact of isoform expression estimation uncertainty. PennDiff is able to detect DAST at both exon and gene levels, thus offering more flexibility than existing methods. Simulations and analysis of a real RNA-seq dataset indicate that PennDiff has well-controlled type I error rate, and is more powerful than existing methods including DEXSeq, rMATS, Cuffdiff, IUTA and SplicingCompass. As the popularity of RNA-seq continues to grow, we expect PennDiff to be useful for diverse transcriptomics studies.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>PennDiff source code and user guide is freely available for download at https:\/\/github.com\/tigerhu15\/PennDiff.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty097","type":"journal-article","created":{"date-parts":[[2018,2,20]],"date-time":"2018-02-20T20:13:52Z","timestamp":1519157632000},"page":"2384-2391","source":"Crossref","is-referenced-by-count":11,"title":["PennDiff: detecting differential alternative splicing and transcription by RNA sequencing"],"prefix":"10.1093","volume":"34","author":[{"given":"Yu","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennie","family":"Lin","sequence":"additional","affiliation":[{"name":"Renal Electrolyte and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Information Theory and Data Science, School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kui","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Information Theory and Data Science, School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanrui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York City, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muredach P","family":"Reilly","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York City, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingyao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,2,20]]},"reference":[{"key":"2023012712591121500_bty097-B1","doi-asserted-by":"crossref","first-page":"R106.","DOI":"10.1186\/gb-2010-11-10-r106","article-title":"Differential expression analysis for sequence count data","volume":"11","author":"Anders","year":"2010","journal-title":"Genome Biol"},{"key":"2023012712591121500_bty097-B2","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1093\/bioinformatics\/btt101","article-title":"SplicingCompass: differential splicing detection using RNA-seq data","volume":"29","author":"Aschoff","year":"2013","journal-title":"Bioinformatics"},{"key":"2023012712591121500_bty097-B3","doi-asserted-by":"crossref","first-page":"10073","DOI":"10.1093\/nar\/gks666","article-title":"Modelling and simulating generic RNA-Seq experiments with the flux simulator","volume":"40","author":"Griebel","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2023012712591121500_bty097-B4","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.tcb.2011.03.003","article-title":"Pre-mRNA splicing: where and when in the nucleus","volume":"21","author":"Han","year":"2011","journal-title":"Trends Cell Biol"},{"key":"2023012712591121500_bty097-B5","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1093\/biostatistics\/kxr025","article-title":"A Gaussian copula approach for the analysis of secondary phenotypes in case-control genetic association studies","volume":"13","author":"He","year":"2012","journal-title":"Biostatistics"},{"key":"2023012712591121500_bty097-B6","doi-asserted-by":"crossref","first-page":"3.","DOI":"10.1186\/1479-7364-8-3","article-title":"A survey of software for genome-wide discovery of differential splicing in RNA-Seq data","volume":"8","author":"Hooper","year":"2014","journal-title":"Hum. 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