Haas, B. J., Dobin, A., Li, B., Stransky, N., Pochet, N., Regev, A. (October 2019) Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods. Genome Biol, 20 (1). p. 213. ISSN 1474-7596
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Abstract
BACKGROUND: Accurate fusion transcript detection is essential for comprehensive characterization of cancer transcriptomes. Over the last decade, multiple bioinformatic tools have been developed to predict fusions from RNA-seq, based on either read mapping or de novo fusion transcript assembly. RESULTS: We benchmark 23 different methods including applications we develop, STAR-Fusion and TrinityFusion, leveraging both simulated and real RNA-seq. Overall, STAR-Fusion, Arriba, and STAR-SEQR are the most accurate and fastest for fusion detection on cancer transcriptomes. CONCLUSION: The lower accuracy of de novo assembly-based methods notwithstanding, they are useful for reconstructing fusion isoforms and tumor viruses, both of which are important in cancer research.
| Item Type: | Paper |
|---|---|
| Additional Information: | Genome biology |
| Uncontrolled Keywords: | *Benchmarking *Cancer *Fusion *RNA-seq *STAR-Fusion *TrinityFusion |
| Subjects: | diseases & disorders > cancer Investigative techniques and equipment bioinformatics > computational biology > algorithms Investigative techniques and equipment > assays Investigative techniques and equipment > assays > RNA-seq |
| CSHL Authors: | |
| Communities: | CSHL labs > Dobin Lab CSHL Cancer Center Program > Cancer Genetics and Genomics Program |
| Depositing User: | Matthew Dunn |
| Date: | 21 October 2019 |
| Date Deposited: | 08 Nov 2019 17:35 |
| Last Modified: | 02 Feb 2024 15:31 |
| PMCID: | PMC6802306 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/38703 |
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