pVACtools is a cancer immunotherapy tools suite consisting of the following tools:

A cancer immunotherapy pipeline for identifying and prioritizing neoantigens from a list of tumor mutations.
A tool for detecting neoantigens resulting from gene fusions.
A tool designed to aid specifically in the construction of DNA-based cancer vaccines.
A browser-based user interface that assists users in launching, managing, reviewing, and visualizing the results of pVACtools processes.
pVACtools immunotherapy workflow

New in version 1.3

This version adds a few features and updates:

  • pVACvector now accepts a list of spacers to use when testing junction epitopes. These can be specified using the --spacers parameter with a comma-separated list of spacer peptides. Including the string None will also test each junction without spacers. The default is None,HH,HHC,HHH,HHHD,HHHC,AAY,HHHH,HHAA,HHL,AAL
  • The --expn-val cutoff parameter has been updated to be a float instead of an integer. This allows the user to provide a decimal cuttoff for the filtering on gene and transcript expression values. Previously, only whole numbers were accepted.
  • Decimal numbers in the pVACseq reports are now rounded to three decimal places. Previously, they were not rounded.

In addition, this version also fixes a few bugs:

  • The --normal-vaf cutoff value was incorrectly defaulting to 0.2 instead of 0.02. This resulted in the coverage filter not being as stringent as it should’ve been.
  • There were a number of bugs in pVACapi and pVACviz that would prevent a user from submitting jobs using the interface in certain conditions. These have been resolved.
  • pVACseq would previsouly not support SVs in the input VCF where the alt had a value of <DEL>. These kinds of variants are now supported.

Past release notes can be found on our Release Notes page.

To stay up-to-date on the latest pVACtools releases please join our Mailing List.


Jasreet Hundal, Susanna Kiwala, Joshua McMichael, Christopher A Miller, Alexander T Wollam, Huiming Xia, Connor J Liu, Sidi Zhao, Yang-Yang Feng, Aaron P Graubert, Amber Z Wollam, Jonas Neichin, Megan Neveau, Jason Walker, William E Gillanders, Elaine R Mardis, Obi L Griffith, Malachi Griffith. pVACtools: a computational toolkit to select and visualize cancer neoantigens. bioRxiv 501817; doi: https://doi.org/10.1101/501817

Jasreet Hundal, Susanna Kiwala, Yang-Yang Feng, Connor J. Liu, Ramaswamy Govindan, William C. Chapman, Ravindra Uppaluri, S. Joshua Swamidass, Obi L. Griffith, Elaine R. Mardis, and Malachi Griffith. Accounting for proximal variants improves neoantigen prediction. Nature Genetics. 2018, DOI: 10.1038/s41588-018-0283-9. PMID: 30510237.

Jasreet Hundal, Beatriz M. Carreno, Allegra A. Petti, Gerald P. Linette, Obi L. Griffith, Elaine R. Mardis, and Malachi Griffith. pVACseq: 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.