nextNEOpi: a comprehensive pipeline for computational neoantigen prediction.

Rieder, Dietmar; Fotakis, Georgios; Ausserhofer, Markus; René, Geyeregger; Paster, Wolfgang; Trajanoski, Zlatko; Finotello, Francesca · Bioinformatics · 2022

basic_science · Level V

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Abstract

Somatic mutations and gene fusions can produce immunogenic neoantigens mediating anticancer immune responses. However, their computational prediction from sequencing data requires complex computational workflows to identify tumor-specific aberrations, derive the resulting peptides, infer patients' Human Leukocyte Antigen types and predict neoepitopes binding to them, together with a set of features underlying their immunogenicity. Here, we present nextNEOpi (nextflow NEOantigen prediction pipeline) a comprehensive and fully automated bioinformatic pipeline to predict tumor neoantigens from raw DNA and RNA sequencing data. In addition, nextNEOpi quantifies neoepitope- and patient-specific features associated with tumor immunogenicity and response to immunotherapy. nextNEOpi source code and documentation are available at https://github.com/icbi-lab/nextNEOpi. dietmar.rieder@i-med.ac.at or francesca.finotello@uibk.ac.at. Supplementary data are available at Bioinformatics online.

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