Bellerophontes: an RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model

Francesco Abate, Andrea Acquaviva, Giulia Paciello, Carmelo Foti, Elisa Ficarra, Alberto Ferrarini, Massimo Delledonne, Ilaria Iacobucci, Simona Soverini, Giovanni Martinelli, Enrico Macii

Abstract: : Next-generation sequencing technology allows the detection of genomic structural variations, novel genes and transcript isoforms from the analysis of high-throughput data. In this work, we propose a new framework for the detection of fusion transcripts through short paired-end reads which integrates splicing-driven alignment and abundance estimation analysis, producing a more accurate set of reads supporting the junction discovery and taking into account also not annotated transcripts. Bellerophontes performs a selection of putative junctions on the basis of a match to an accurate gene fusion model.