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nextNEOpi: a comprehensive pipeline for computational neoantigen prediction

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 pa...

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Autores principales: Rieder, Dietmar, Fotakis, Georgios, Ausserhofer, Markus, René, Geyeregger, Paster, Wolfgang, Trajanoski, Zlatko, Finotello, Francesca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8796378/
https://www.ncbi.nlm.nih.gov/pubmed/34788790
http://dx.doi.org/10.1093/bioinformatics/btab759
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author Rieder, Dietmar
Fotakis, Georgios
Ausserhofer, Markus
René, Geyeregger
Paster, Wolfgang
Trajanoski, Zlatko
Finotello, Francesca
author_facet Rieder, Dietmar
Fotakis, Georgios
Ausserhofer, Markus
René, Geyeregger
Paster, Wolfgang
Trajanoski, Zlatko
Finotello, Francesca
author_sort Rieder, Dietmar
collection PubMed
description 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.
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spelling pubmed-87963782022-01-31 nextNEOpi: a comprehensive pipeline for computational neoantigen prediction Rieder, Dietmar Fotakis, Georgios Ausserhofer, Markus René, Geyeregger Paster, Wolfgang Trajanoski, Zlatko Finotello, Francesca Bioinformatics Applications Notes 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 2021-11-12 /pmc/articles/PMC8796378/ /pubmed/34788790 http://dx.doi.org/10.1093/bioinformatics/btab759 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Rieder, Dietmar
Fotakis, Georgios
Ausserhofer, Markus
René, Geyeregger
Paster, Wolfgang
Trajanoski, Zlatko
Finotello, Francesca
nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title_full nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title_fullStr nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title_full_unstemmed nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title_short nextNEOpi: a comprehensive pipeline for computational neoantigen prediction
title_sort nextneopi: a comprehensive pipeline for computational neoantigen prediction
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8796378/
https://www.ncbi.nlm.nih.gov/pubmed/34788790
http://dx.doi.org/10.1093/bioinformatics/btab759
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