NeoFuse – predicting fusion neoantigens from RNA sequencing data

Gene fusions can generate immunogenic neoantigens that mediate anticancer immune responses. However, their computational prediction from RNA sequencing (RNA-seq) data requires deep bioinformatics expertise to assembly a computational workflow covering the prediction of: fusion transcripts, their translated proteins and peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity. Here, researchers from the Medical University of Innsbruck present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq dataNeoFuse can be applied to cancer patients’ RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy.


Pipeline Scheme

Availability – NeoFuse source code and documentation are available under GPLv3 license at

Fotakis G, Rieder D, Haider M, Trajanoski Z, Finotello F. (2019) NeoFuse: predicting fusion neoantigens from RNA sequencing data. Bioinformatics [Epub ahead of print]. [abstract]

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