RT Journal Article SR Electronic T1 STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq JF bioRxiv FD Cold Spring Harbor Laboratory SP 120295 DO 10.1101/120295 A1 Brian J. Haas A1 Alex Dobin A1 Nicolas Stransky A1 Bo Li A1 Xiao Yang A1 Timothy Tickle A1 Asma Bankapur A1 Carrie Ganote A1 Thomas G. Doak A1 Nathalie Pochet A1 Jing Sun A1 Catherine J. Wu A1 Thomas R. Gingeras A1 Aviv Regev YR 2017 UL http://biorxiv.org/content/early/2017/03/24/120295.abstract AB 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