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.