NeoFuse: predicting fusion neoantigens from RNA sequencing data

Abstract

Summary: 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, we present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq data. NeoFuse can be applied to cancer patients' RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy.

Availability and implementation: NeoFuse source code and documentation are available under GPLv3 license at https://icbi.i-med.ac.at/NeoFuse/.

Supplementary information: Supplementary data are available at Bioinformatics online.