nextNEOpi: a comprehensive pipeline for computational neoantigen prediction

D Rieder, G Fotakis, M Ausserhofer, G Rene… - …, 2022 - academic.oup.com
D Rieder, G Fotakis, M Ausserhofer, G Rene, W Paster, Z Trajanoski, F Finotello
Bioinformatics, 2022academic.oup.com
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 (next flow NEO antigen prediction pi peline) a comprehensive …
Summary
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.
Availability and implementation
nextNEOpi source code and documentation are available at https://github.com/icbi-lab/nextNEOpi
Contact
dietmar.rieder@i-med.ac.at or francesca.finotello@uibk.ac.at
Supplementary information
Supplementary data are available at Bioinformatics online.
Oxford University Press