pVAC-Seq is a cancer immunotherapy pipeline for the identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation and expression data (DNA- and RNA-Seq). It enables cancer immunotherapy research by using massively parallel sequence data to predicting tumor-specific mutant peptides (neoantigens) that can elicit anti-tumor T cell immunity. It is being used in studies of checkpoint therapy response and to identify targets for cancer vaccines and adoptive T cell therapies. For more general information, see the manuscript published in Genome Medicine.

New in version 4.0.7

This version improves the sorting of the final report file. The file will now be sorted by “Gene Name” and “Mutation” and within these categories by the MT score - either “Median MT Score” or “Best MT score” depending on the top-score-metric used.

This release implements a 60 second wait between each request to the IEDB RESTful API in order to decrease the load on their servers. We recommend the usage of the standalone IEDB tools for long-running processes with many variants, prediction algorithm, epitope lengths, or alleles.

There also have been various bugfixes in this release.


Jasreet Hundal, Beatriz M. Carreno, Allegra A. Petti, Gerald P. Linette, Obi L. Griffith, Elaine R. Mardis, and Malachi Griffith. pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens. Genome Medicine. 2016, 8:11, DOI: 10.1186/s13073-016-0264-5. PMID: 26825632.


This project is licensed under NPOSL-3.0.