TY - JOUR T1 - STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq JF - bioRxiv DO - 10.1101/120295 SP - 120295 AU - Brian J. Haas AU - Alex Dobin AU - Nicolas Stransky AU - Bo Li AU - Xiao Yang AU - Timothy Tickle AU - Asma Bankapur AU - Carrie Ganote AU - Thomas G. Doak AU - Nathalie Pochet AU - Jing Sun AU - Catherine J. Wu AU - Thomas R. Gingeras AU - Aviv Regev Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/03/24/120295.abstract N2 - Motivation Fusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data.Results We benchmarked STAR-Fusion’s fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods.Availability and implementation STAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux.Contact bhaas{at}broadinstitute.org ER -