@inbook{5bc41429c2ae48b28b63b78b7a879a0b,
title = "OpenVax: An open-source computational pipeline for cancer neoantigen prediction",
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",
author = "Julia Kodysh and Alex Rubinsteyn",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC, part of Springer Nature 2020.",
year = "2020",
doi = "10.1007/978-1-0716-0327-7_10",
language = "English",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "147--160",
booktitle = "Methods in Molecular Biology",
}