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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.

SUBMITTER: Fotakis G 

PROVIDER: S-EPMC7141848 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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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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