OpenVax: An Open-Source Computational Pipeline for Cancer Neoantigen Prediction

Julia Kodysh; Alex Rubinsteyn

doi:10.1007/978-1-0716-0327-7_10

OpenVax: An Open-Source Computational Pipeline for Cancer Neoantigen Prediction

Methods Mol Biol. 2020:2120:147-160. doi: 10.1007/978-1-0716-0327-7_10.

Authors

Julia Kodysh¹, Alex Rubinsteyn²

Affiliations

¹ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. julia@openvax.org.
² Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

PMID: 32124317
DOI: 10.1007/978-1-0716-0327-7_10

Abstract

OpenVax is a computational workflow for identifying somatic variants, predicting neoantigens, and selecting the contents of personalized cancer vaccines. It is a Dockerized end-to-end pipeline that takes as input raw tumor/normal sequencing data. It is currently used in three clinical trials (NCT02721043, NCT03223103, and NCT03359239). In this chapter, we describe how to install and use OpenVax, as well as how to interpret the generated results.

Keywords: Bioinformatics pipeline; Cancer vaccine; Docker; Immunoinformatics; NGS; Neoantigen.

MeSH terms

Antigens, Neoplasm / genetics*
Cancer Vaccines / genetics
Genetic Variation
Genomics / methods*
High-Throughput Nucleotide Sequencing / methods
Humans
Neoplasms / genetics*
Software*
Workflow

Substances

Antigens, Neoplasm
Cancer Vaccines