{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,12]],"date-time":"2026-11-12T09:06:10Z","timestamp":1794474370726,"version":"4.9.1"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T00:00:00Z","timestamp":1681171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 HG009937"],"award-info":[{"award-number":["R01 HG009937"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["T32 CA106209"],"award-info":[{"award-number":["T32 CA106209"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["U01 CA274298"],"award-info":[{"award-number":["U01 CA274298"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["P50 CA257911"],"award-info":[{"award-number":["P50 CA257911"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["P50 CA058223"],"award-info":[{"award-number":["P50 CA058223"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,4,15]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses. This procedure leverages fast matrix-based computations that make it ideally suited for DTU analysis with larger sample sizes. This method also allows for the testing of and adjustment for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty in the expression estimates for each transcript in RNA-seq data. We extend our CompDTU method to incorporate quantification uncertainty leveraging common output from RNA-seq expression quantification tool in a novel method CompDTUme. Through several power analyses, we show that CompDTU has excellent sensitivity and reduces false positive results relative to existing methods. Additionally, CompDTUme results in further improvements in performance over CompDTU with sufficient sample size for genes with high levels of quantification uncertainty, while also maintaining favorable speed and scalability. We motivate our methods using data from the Cancer Genome Atlas Breast Invasive Carcinoma data set, specifically using RNA-seq data from primary tumors for 740 patients with breast cancer. We show greatly reduced computation time from our new methods as well as the ability to detect several novel genes with significant DTU across different breast cancer subtypes.<\/jats:p>","DOI":"10.1093\/biostatistics\/kxad008","type":"journal-article","created":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T22:30:41Z","timestamp":1681252241000},"page":"559-576","source":"Crossref","is-referenced-by-count":2,"title":["Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling"],"prefix":"10.1093","volume":"25","author":[{"given":"Amber M","family":"Young","sequence":"first","affiliation":[{"name":"University of North Carolina at Chapel Hill Department of Biostatistics, , 135 Dauer Drive, Chapel Hill, NC, 27599, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5722-4342","authenticated-orcid":false,"given":"Scott","family":"Van Buren","sequence":"additional","affiliation":[{"name":"University of North Carolina at Chapel Hill Department of Biostatistics, , 135 Dauer Drive, Chapel Hill, NC, 27599, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naim U","family":"Rashid","sequence":"additional","affiliation":[{"name":"University of North Carolina at Chapel Hill Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC, 27599, USA and Lineberger Comprehensive Cancer Center, , 450 West Drive, Chapel Hill, NC, 27599, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"2024041508011316700_B1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1111\/j.2517-6161.1982.tb01195.x","article-title":"The statistical analysis of compositional data","volume":"44","author":"Aitchison,","year":"1982","journal-title":"Journal of the Royal Statistical Society. 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