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ABSTRACT: 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 (HLA) types, and predict neoepitopes binding to them, together with a set of features underlying their immunogenicity. Here, we present nextNEOpi, 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.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Rieder D
PROVIDER: S-EPMC8796378 | biostudies-literature |
REPOSITORIES: biostudies-literature