Fusionanalyser: a new graphical, event-driven tool for fusion rearrangements discovery

Gene fusions are common driver events in leukae-mias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identifica-tion of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We ini-tially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2–ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearran-gements in the context of high-throughput tran-scriptome sequencing data