NeoFuse: predicting fusion neoantigens from RNA sequencing data.
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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.
SUBMITTER: Fotakis G
PROVIDER: S-EPMC7141848 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
NeoFuse: predicting fusion neoantigens from RNA sequencing data.
Fotakis Georgios G Rieder Dietmar D Haider Marlene M Trajanoski Zlatko Z Finotello Francesca F
Bioinformatics (Oxford, England) 20200401 7
<h4>Summary</h4>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 ne ...[more]
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