{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T03:55:50Z","timestamp":1774670150039,"version":"3.50.1"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2020,7,13]],"date-time":"2020-07-13T00:00:00Z","timestamp":1594598400000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Institute of Health","award":["R01 HG009937"],"award-info":[{"award-number":["R01 HG009937"]}]},{"name":"National Institute of Health","award":["R01 MH118349"],"award-info":[{"award-number":["R01 MH118349"]}]},{"name":"National Institute of Health","award":["P01 CA142538"],"award-info":[{"award-number":["P01 CA142538"]}]},{"name":"National Institute of Health","award":["P30 365 ES010126"],"award-info":[{"award-number":["P30 365 ES010126"]}]},{"name":"National Institute of Health","award":["R01 GM114267"],"award-info":[{"award-number":["R01 GM114267"]}]},{"name":"National Institute of Health","award":["R24 MH114815"],"award-info":[{"award-number":["R24 MH114815"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CCF-1750472"],"award-info":[{"award-number":["CCF-1750472"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1763680"],"award-info":[{"award-number":["CNS-1763680"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Advances in sequencing technology, inference algorithms and differential testing methodology have enabled transcript-level analysis of RNA-seq data. Yet, the inherent inferential uncertainty in transcript-level abundance estimation, even among the most accurate approaches, means that robust transcript-level analysis often remains a challenge. Conversely, gene-level analysis remains a common and robust approach for understanding RNA-seq data, but it coarsens the resulting analysis to the level of genes, even if the data strongly support specific transcript-level effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We introduce a new data-driven approach for grouping together transcripts in an experiment based on their inferential uncertainty. Transcripts that share large numbers of ambiguously-mapping fragments with other transcripts, in complex patterns, often cannot have their abundances confidently estimated. Yet, the total transcriptional output of that group of transcripts will have greatly reduced inferential uncertainty, thus allowing more robust and confident downstream analysis. Our approach, implemented in the tool terminus, groups together transcripts in a data-driven manner allowing transcript-level analysis where it can be confidently supported, and deriving transcriptional groups where the inferential uncertainty is too high to support a transcript-level result.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Terminus is implemented in Rust, and is freely available and open source. It can be obtained from https:\/\/github.com\/COMBINE-lab\/Terminus.<\/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\/btaa448","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T15:13:59Z","timestamp":1591283639000},"page":"i102-i110","source":"Crossref","is-referenced-by-count":18,"title":["Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data"],"prefix":"10.1093","volume":"36","author":[{"given":"Hirak","family":"Sarkar","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"}]},{"given":"Avi","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stony Brook University , Stony Brook, NY 11794, USA"}]},{"given":"H\u00e9ctor Corrada","family":"Bravo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"}]},{"given":"Michael I","family":"Love","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of North Carolina-Chapel Hill , Chapel Hill, NC 27516, USA"},{"name":"Department of Genetics, University of North Carolina-Chapel Hill , Chapel Hill, NC 27514, USA"}]},{"given":"Rob","family":"Patro","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,7,13]]},"reference":[{"key":"2024021913324106400_btaa448-B1","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1471-2164-15-S8-S2","article-title":"Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates","volume":"15","author":"Al Seesi","year":"2014","journal-title":"BMC Genomics"},{"key":"2024021913324106400_btaa448-B2","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1101\/gr.108662.110","article-title":"Conservation of an RNA regulatory map between Drosophila and mammals","volume":"21","author":"Brooks","year":"2011","journal-title":"Genome Res"},{"key":"2024021913324106400_btaa448-B3","volume-title":"Introduction to Algorithms","author":"Cormen","year":"2009"},{"key":"2024021913324106400_btaa448-B4","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1093\/bioinformatics\/btt591","article-title":"ORMAN: optimal resolution of ambiguous RNA-Seq multimappings in the presence of novel isoforms","volume":"30","author":"Dao","year":"2014","journal-title":"Bioinformatics"},{"key":"2024021913324106400_btaa448-B5","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1093\/bioinformatics\/bts635","article-title":"STAR: ultrafast universal RNA-seq aligner","volume":"29","author":"Dobin","year":"2013","journal-title":"Bioinformatics"},{"key":"2024021913324106400_btaa448-B6","doi-asserted-by":"crossref","first-page":"2778","DOI":"10.1093\/bioinformatics\/btv272","article-title":"Polyester: simulating RNA-seq datasets with differential transcript expression","volume":"31","author":"Frazee","year":"2015","journal-title":"Bioinformatics"},{"key":"2024021913324106400_btaa448-B7","first-page":"209","author":"Garland","year":"1997"},{"key":"2024021913324106400_btaa448-B8","doi-asserted-by":"crossref","first-page":"e1006464","DOI":"10.1371\/journal.pgen.1006464","article-title":"Alternative splicing within and between drosophila species, sexes, tissues, and developmental stages","volume":"12","author":"Gibilisco","year":"2016","journal-title":"PLoS Genet"},{"key":"2024021913324106400_btaa448-B9","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":"2024021913324106400_btaa448-B10","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. 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