Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods

Brian J. Haas, Alexander Dobin, Bo Li, Nicolas Stransky, Nathalie Pochet, Aviv Regev

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number213
JournalGenome Biology
Volume20
Issue number1
DOIs
StatePublished - Oct 21 2019

Fingerprint

accuracy assessment
cancer
Transcriptome
neoplasms
RNA
transcriptome
Benchmarking
Neoplasms
Oncogenic Viruses
bioinformatics
Computational Biology
tumor
virus
Protein Isoforms
methodology
application methods
Research
viruses
detection
method

Keywords

  • Benchmarking
  • Cancer
  • Fusion
  • RNA-seq
  • STAR-Fusion
  • TrinityFusion

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

Cite this

Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods. / Haas, Brian J.; Dobin, Alexander; Li, Bo; Stransky, Nicolas; Pochet, Nathalie; Regev, Aviv.

In: Genome Biology, Vol. 20, No. 1, 213, 21.10.2019.

Research output: Contribution to journalArticle

Haas, Brian J. ; Dobin, Alexander ; Li, Bo ; Stransky, Nicolas ; Pochet, Nathalie ; Regev, Aviv. / Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods. In: Genome Biology. 2019 ; Vol. 20, No. 1.
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