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 4.0.9

This release adds handling for DNPs and MNPs missense mutations.

This version adds a new option --additonal-report-columns to the pvacseq run command which can be use to append additional columns of data to the report. Right now the only value supported for this option is sample_name which appends a column with the sample name to the final report.

We updated the logic that determines whether or not a corresponding wildtype epitope for a mutant epitope is included in the report. Previously, we would only include the corresponding wildtype epitope if the number of consecutive matching amino acids between mutant and wildtype epitope was larger then half of the total number of amino acids in the epitope. We now use the total number of matching amino acids between the mutant epitope and the corespondig wildtype epitope across the whole length of the epitope to make that determination. The total number of matching amino acids needs to be larger than half of the length of the epitope. Otherwise the corresponding wildtype epitope is reported as “NA”.

With this release any execution of pvacseq run will create a log file of the inputs used. This log file is then used when executing another run with the same output directory. This ensures that you can only write to the same output directory if identical parameters are used.


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.