nextNEOpi: a comprehensive pipeline for computational neoantigen prediction.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 34788790.
- Also identified by DOI 10.1093/bioinformatics/btab759 and PMC identifier 8796378.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Neoplasms