{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T13:10:34Z","timestamp":1649164234870},"reference-count":10,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2019,6]]},"abstract":"<jats:p> Fusion genes are involved in cancer, and their detection using RNA-Seq is insufficient given the relatively short reading length. Therefore, we proposed a shifted short-read clustering (SSC) method, which focuses on overlapping reads from the same loci and extends them as a representative sequence. To verify their usefulness, we applied the SSC method to RNA-Seq data from four types of cell lines (BT-474, MCF-7, SKBR-3, and T-47D). As the slide width of the SSC method increased to one, two, five, or ten bases, the read length was extended from 201 bases to 217 (108%), 234 (116%), 282 (140%), or 317 (158%) bases, respectively. Furthermore, fusion genes were investigated using STAR-Fusion, a fusion gene detection tool, with and without the SSC method. When one base was shifted by the SSC method, the reads mapped to multiple loci decreased from 9.7% to 4.6%, and the sensitivity of the fusion gene was improved from 47% to 54% on average (BT-474: from 48% to 57%, MCF-7: 49% to 53%, SKBR-3: 50% to 57%, and T-47D: 43% to 50%) compared with original data. When the reads are shifted more, the positive predictive value was also improved. The SSC method could be an effective method for fusion gene detection. <\/jats:p>","DOI":"10.1142\/s0219720019400080","type":"journal-article","created":{"date-parts":[[2019,5,10]],"date-time":"2019-05-10T05:44:12Z","timestamp":1557467052000},"page":"1940008","source":"Crossref","is-referenced-by-count":1,"title":["Improvement of detection performance of fusion genes from RNA-seq data by clustering short reads"],"prefix":"10.1142","volume":"17","author":[{"given":"Yoshiaki","family":"Sota","sequence":"first","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, 1-15 Yamadaoka, Suita, Osaka 565-0871, Japan"},{"name":"Graduate School of Medicine, Osaka University, 2-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Shigeto","family":"Seno","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, 1-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Hironori","family":"Shigeta","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, 1-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Naoki","family":"Osato","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, 1-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Masafumi","family":"Shimoda","sequence":"additional","affiliation":[{"name":"Graduate School of Medicine, Osaka University, 2-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Shinzaburo","family":"Noguchi","sequence":"additional","affiliation":[{"name":"Graduate School of Medicine, Osaka University, 2-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]},{"given":"Hideo","family":"Matsuda","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, 1-15 Yamadaoka, Suita, Osaka 565-0871, Japan"}]}],"member":"219","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"S0219720019400080BIB001","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu170"},{"key":"S0219720019400080BIB002","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2011-12-1-r6"},{"key":"S0219720019400080BIB003","first-page":"120295","author":"Haas B","year":"2017","journal-title":"BioRxiv"},{"key":"S0219720019400080BIB004","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0048745"},{"key":"S0219720019400080BIB005","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-016-0001-8","volume":"6","author":"Kumar S","year":"2016","journal-title":"Sci. Rep."},{"issue":"699","key":"S0219720019400080BIB006","first-page":"1","volume":"15","author":"Miyamoto M","year":"2014","journal-title":"BMC Genomics"},{"key":"S0219720019400080BIB007","doi-asserted-by":"publisher","DOI":"10.15252\/emmm.201404913"},{"key":"S0219720019400080BIB008","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq677"},{"key":"S0219720019400080BIB009","doi-asserted-by":"publisher","DOI":"10.1038\/nature05945"},{"key":"S0219720019400080BIB010","first-page":"380","volume-title":"Proc Int Conf Bioinformatics & Computational Biology (BIOCOMP)","author":"Suzuki K","year":"2013"}],"container-title":["Journal of Bioinformatics and Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0219720019400080","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T17:16:50Z","timestamp":1565111810000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0219720019400080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6]]},"references-count":10,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2019,7,9]]},"published-print":{"date-parts":[[2019,6]]}},"alternative-id":["10.1142\/S0219720019400080"],"URL":"https:\/\/doi.org\/10.1142\/s0219720019400080","relation":{},"ISSN":["0219-7200","1757-6334"],"issn-type":[{"value":"0219-7200","type":"print"},{"value":"1757-6334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6]]}}}