Related Experiment Video
Updated: Jan 5, 2026
Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
Published on: August 4, 2016
Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based
Brian J Haas1, Alexander Dobin2, Bo Li3,4
1Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. bhaas@broadinstitute.org.
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.
Related Concept Videos
03:21RNA-seq
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
03:36Genome Annotation and Assembly