{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T21:20:34Z","timestamp":1717190434777},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,4,15]]},"abstract":"Abstract<\/jats:title>\n Summary: A new generation of tools that identify fusion genes in RNA-seq data is limited in either sensitivity and or specificity. To allow further downstream analysis and to estimate performance, predicted fusion genes from different tools have to be compared. However, the transcriptomic context complicates genomic location-based matching. FusionMatcher (FuMa) is a program that reports identical fusion genes based on gene-name annotations. FuMa automatically compares and summarizes all combinations of two or more datasets in a single run, without additional programming necessary. FuMa uses one gene annotation, avoiding mismatches caused by tool-specific gene annotations. FuMa matches 10% more fusion genes compared with exact gene matching due to overlapping genes and accepts intermediate output files that allow a stepwise analysis of corresponding tools.<\/jats:p>\n Availability and implementation: The code is available at: https:\/\/github.com\/ErasmusMC-Bioinformatics\/fuma and available for Galaxy in the tool sheds and directly accessible at https:\/\/bioinf-galaxian.erasmusmc.nl\/galaxy\/<\/jats:p>\n Contact: \u00a0y.hoogstrate@erasmusmc.nl or a.stubbs@erasmusmc.nl<\/jats:p>\n Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv721","type":"journal-article","created":{"date-parts":[[2015,12,12]],"date-time":"2015-12-12T01:49:22Z","timestamp":1449884962000},"page":"1226-1228","source":"Crossref","is-referenced-by-count":5,"title":["FuMa: reporting overlap in RNA-seq detected fusion genes"],"prefix":"10.1093","volume":"32","author":[{"given":"Youri","family":"Hoogstrate","sequence":"first","affiliation":[{"name":"1 Department of Urology and"},{"name":"2 Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands"}]},{"given":"Ren\u00e9","family":"B\u00f6ttcher","sequence":"additional","affiliation":[{"name":"1 Department of Urology and"}]},{"given":"Saskia","family":"Hiltemann","sequence":"additional","affiliation":[{"name":"1 Department of Urology and"},{"name":"2 Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands"}]},{"given":"Peter J.","family":"van der Spek","sequence":"additional","affiliation":[{"name":"2 Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands"}]},{"given":"Guido","family":"Jenster","sequence":"additional","affiliation":[{"name":"1 Department of Urology and"}]},{"given":"Andrew P.","family":"Stubbs","sequence":"additional","affiliation":[{"name":"2 Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands"}]}],"member":"286","published-online":{"date-parts":[[2015,12,10]]},"reference":[{"key":"2023020112195657900_btv721-B1","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1093\/bioinformatics\/btu638","article-title":"Htseq-a python framework to work with high-throughput sequencing data","volume":"31","author":"Anders","year":"2015","journal-title":"Bioinformatics"},{"key":"2023020112195657900_btv721-B2","doi-asserted-by":"crossref","first-page":"3556","DOI":"10.1093\/bioinformatics\/btu662","article-title":"Chimera: a bioconductor package for secondary analysis of fusion products","volume":"30","author":"Beccuti","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020112195657900_btv721-B3","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1101\/gr.103697.109","article-title":"Integrative analysis of the melanoma transcriptome","volume":"20","author":"Berger","year":"2010","journal-title":"Genome Res"},{"issue":"Suppl 7","key":"2023020112195657900_btv721-B4","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1471-2105-14-S7-S2","article-title":"State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues?","volume":"14","author":"Carrara","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2023020112195657900_btv721-B5","doi-asserted-by":"crossref","first-page":"R6","DOI":"10.1186\/gb-2011-12-1-r6","article-title":"Identification of fusion genes in breast cancer by paired-end RNA-sequencing","volume":"12","author":"Edgren","year":"2011","journal-title":"Genome Biol"},{"key":"2023020112195657900_btv721-B6","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1038\/nmeth.3407","article-title":"Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection","volume":"12","author":"Ewing","year":"2015","journal-title":"Nat. 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