Literature DB >> 21330288

Sensitive gene fusion detection using ambiguously mapping RNA-Seq read pairs.

Marcus Kinsella1, Olivier Harismendy, Masakazu Nakano, Kelly A Frazer, Vineet Bafna.   

Abstract

MOTIVATION: Paired-end whole transcriptome sequencing provides evidence for fusion transcripts. However, due to the repetitiveness of the transcriptome, many reads have multiple high-quality mappings. Previous methods to find gene fusions either ignored these reads or required additional longer single reads. This can obscure up to 30% of fusions and unnecessarily discards much of the data.
RESULTS: We present a method for using paired-end reads to find fusion transcripts without requiring unique mappings or additional single read sequencing. Using simulated data and data from tumors and cell lines, we show that our method can find fusions with ambiguously mapping read pairs without generating numerous spurious fusions from the many mapping locations. AVAILABILITY: A C++ and Python implementation of the method demonstrated in this article is available at http://exon.ucsd.edu/ShortFuse. CONTACT: mckinsel@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2011        PMID: 21330288      PMCID: PMC3072550          DOI: 10.1093/bioinformatics/btr085

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  35 in total

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4.  Fused transcript of abl and bcr genes in chronic myelogenous leukaemia.

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Authors:  P Carninci; T Kasukawa; S Katayama; J Gough; M C Frith; N Maeda; R Oyama; T Ravasi; B Lenhard; C Wells; R Kodzius; K Shimokawa; V B Bajic; S E Brenner; S Batalov; A R R Forrest; M Zavolan; M J Davis; L G Wilming; V Aidinis; J E Allen; A Ambesi-Impiombato; R Apweiler; R N Aturaliya; T L Bailey; M Bansal; L Baxter; K W Beisel; T Bersano; H Bono; A M Chalk; K P Chiu; V Choudhary; A Christoffels; D R Clutterbuck; M L Crowe; E Dalla; B P Dalrymple; B de Bono; G Della Gatta; D di Bernardo; T Down; P Engstrom; M Fagiolini; G Faulkner; C F Fletcher; T Fukushima; M Furuno; S Futaki; M Gariboldi; P Georgii-Hemming; T R Gingeras; T Gojobori; R E Green; S Gustincich; M Harbers; Y Hayashi; T K Hensch; N Hirokawa; D Hill; L Huminiecki; M Iacono; K Ikeo; A Iwama; T Ishikawa; M Jakt; A Kanapin; M Katoh; Y Kawasawa; J Kelso; H Kitamura; H Kitano; G Kollias; S P T Krishnan; A Kruger; S K Kummerfeld; I V Kurochkin; L F Lareau; D Lazarevic; L Lipovich; J Liu; S Liuni; S McWilliam; M Madan Babu; M Madera; L Marchionni; H Matsuda; S Matsuzawa; H Miki; F Mignone; S Miyake; K Morris; S Mottagui-Tabar; N Mulder; N Nakano; H Nakauchi; P Ng; R Nilsson; S Nishiguchi; S Nishikawa; F Nori; O Ohara; Y Okazaki; V Orlando; K C Pang; W J Pavan; G Pavesi; G Pesole; N Petrovsky; S Piazza; J Reed; J F Reid; B Z Ring; M Ringwald; B Rost; Y Ruan; S L Salzberg; A Sandelin; C Schneider; C Schönbach; K Sekiguchi; C A M Semple; S Seno; L Sessa; Y Sheng; Y Shibata; H Shimada; K Shimada; D Silva; B Sinclair; S Sperling; E Stupka; K Sugiura; R Sultana; Y Takenaka; K Taki; K Tammoja; S L Tan; S Tang; M S Taylor; J Tegner; S A Teichmann; H R Ueda; E van Nimwegen; R Verardo; C L Wei; K Yagi; H Yamanishi; E Zabarovsky; S Zhu; A Zimmer; W Hide; C Bult; S M Grimmond; R D Teasdale; E T Liu; V Brusic; J Quackenbush; C Wahlestedt; J S Mattick; D A Hume; C Kai; D Sasaki; Y Tomaru; S Fukuda; M Kanamori-Katayama; M Suzuki; J Aoki; T Arakawa; J Iida; K Imamura; M Itoh; T Kato; H Kawaji; N Kawagashira; T Kawashima; M Kojima; S Kondo; H Konno; K Nakano; N Ninomiya; T Nishio; M Okada; C Plessy; K Shibata; T Shiraki; S Suzuki; M Tagami; K Waki; A Watahiki; Y Okamura-Oho; H Suzuki; J Kawai; Y Hayashizaki
Journal:  Science       Date:  2005-09-02       Impact factor: 47.728

9.  Evidence for trans splicing in trypanosomes.

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  29 in total

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Review 2.  Next-generation transcriptome assembly.

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Review 3.  Detecting and targetting oncogenic fusion proteins in the genomic era.

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Review 4.  Next-generation sequencing in the clinic: promises and challenges.

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Review 5.  Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives.

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Review 6.  Identification of cancer gene fusions based on advanced analysis of the human genome or transcriptome.

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Review 7.  Identifying fusion transcripts using next generation sequencing.

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8.  Long-range transcriptome sequencing reveals cancer cell growth regulatory chimeric mRNA.

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10.  Gene Fusion Markup Language: a prototype for exchanging gene fusion data.

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