{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:54Z","timestamp":1772138094407,"version":"3.50.1"},"reference-count":9,"publisher":"Oxford University Press (OUP)","issue":"20","license":[{"start":{"date-parts":[[2019,3,11]],"date-time":"2019-03-11T00:00:00Z","timestamp":1552262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM126019"],"award-info":[{"award-number":["R01GM126019"]}],"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":["U54HL127624"],"award-info":[{"award-number":["U54HL127624"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"AMEDD Advanced Medical Technology Initiative; and National Institutes of Health","award":["U54HG008098"],"award-info":[{"award-number":["U54HG008098"]}]},{"name":"AWS Cloud Credits for Research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>For many next generation-sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner is optimized for speed and is often executed in parallel on the cloud. However, there are other less demanding steps that can also be optimized to significantly increase the speed especially when using many threads. We demonstrate this using a unique molecular identifier RNA-sequencing pipeline consisting of 3 steps: split, align, and merge. Optimization of all three steps yields a 40% increase in speed when executed using a single thread. However, when executed using 16 threads, we observe a 4-fold improvement over the original parallel implementation and more than an 8-fold improvement over the original single-threaded implementation. In contrast, optimizing only the alignment step results in just a 13% improvement over the original parallel workflow using 16 threads.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Code (M.I.T. license), supporting scripts and Dockerfiles are available at https:\/\/github.com\/BioDepot\/LINCS_RNAseq_cpp and Docker images at https:\/\/hub.docker.com\/r\/biodepot\/rnaseq-umi-cpp\/<\/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\/btz169","type":"journal-article","created":{"date-parts":[[2019,3,9]],"date-time":"2019-03-09T07:09:47Z","timestamp":1552115387000},"page":"4173-4175","source":"Crossref","is-referenced-by-count":5,"title":["Holistic optimization of an RNA-seq workflow for multi-threaded environments"],"prefix":"10.1093","volume":"35","author":[{"given":"Ling-Hong","family":"Hung","sequence":"first","affiliation":[{"name":"School of Engineering and Technology , Tacoma, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wes","family":"Lloyd","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology , Tacoma, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Radhika","family":"Agumbe Sridhar","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology , Tacoma, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saranya Devi","family":"Athmalingam Ravishankar","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology , Tacoma, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuguang","family":"Xiong","sequence":"additional","affiliation":[{"name":"Ichahn School of Medicine at Mount Sinai , New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Sobie","sequence":"additional","affiliation":[{"name":"Ichahn School of Medicine at Mount Sinai , New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1754-7577","authenticated-orcid":false,"given":"Ka Yee","family":"Yeung","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology , Tacoma, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,3,11]]},"reference":[{"key":"2023013108272072200_btz169-B1","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1145\/1465482.1465560","volume-title":"Proceedings of the April 18-20, 1967, Spring Joint Computer Conference, AFIPS \u201967 (Spring)","author":"Amdahl","year":"1967"},{"key":"2023013108272072200_btz169-B2","doi-asserted-by":"crossref","first-page":"D991","DOI":"10.1093\/nar\/gks1193","article-title":"NCBI GEO: archive for functional genomics data sets\u2013update","volume":"41","author":"Barrett","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2023013108272072200_btz169-B3","doi-asserted-by":"crossref","first-page":"525.","DOI":"10.1038\/nbt.3519","article-title":"Near-optimal probabilistic rna-seq quantification","volume":"34","author":"Bray","year":"2016","journal-title":"Nat. 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