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 1.1.5

This is a hotfix release. It fixes the following issue(s):

  • When running pVACseq with a phased input VCF the mutation position offset of a framshift somatic variant to their proximal variants was not getting calculated correctly, leading to errors.
  • For running pVACvector we removed a dependency on a commandline tool by using a python library instead. This allowed us to remove a system call to a tool that required standalone installation by the user.

New in version 1.1.4

This is a hotfix release. It fixes the following issue(s):

  • When running pVACvector with a with a pVACseq input file and the corresponding VCF, the sample name wasn’t being passed along correctly which would cause an error if the input VCF was a multi-sample VCF.
  • pVACseq would throw an error if the value of a gene or transcript expression field was empty.

New in version 1.1.3

This is a hotfix release. It fixes the following issue(s):

  • When using the MHCnuggets prediction algorithm for MHC class II alleles (MHCnuggetsII) not all epitope sequences were predicted for inframe insertions. This issues has now been fixed.
  • For MHCflurry cases with peptide sequences that were shorter than the desired epitope length were not handled correctly which resulted in an error. This issues has been resolved in this release.

New in version 1.1.2

This is a hotfix release. It fixes the following issue(s):

  • In version 1.1.0 we added a --pass-only flag to pVACseq that would result in only variants with FILTER of PASS or . getting processed. However, this option was not getting passed along to the pVACseq process correctly, resulting in this option not taking effect. This hotfix release fixes this issue and the --pass-only flag should now work as expected.

New in version 1.1.1

This is a hotfix release. It fixes the following issue(s):

  • In version 1.1 we updated VAFs to be fractions, rather than percentages. A bug in this code change resulted in an error when using custom VAF cutoff values instead of the default. This has now been fixed.

New in version 1.1

This version adds a host of new features to pVACtools:

  • pVACseq is now able to parse VAF, depth, and expression information directly from the VCF. This makes the --additional-input-file-list option obsolete. The --additional-input-file-list option is now deprecated and will be removed in an upcoming release. For more information on how to annotate your VCF with readcount and expression information, see the Input File Preparation page.
  • pVACseq is now able to handle proximal germline and somatic variants. In order to incorporate those into the epitope predictions, you will need to provide a phased variants VCF to your pVACseq run using the --phased-proximal-variants-vcf option. For more information on how to create this file, see the Input File Preparation page.
  • We added support to pVACseq for filtering on transcript support levels. This requires the input VCF to be annotated with the TSL field by VEP. Be default, any transcripts with a TSL above 1 will be filtered out.
  • The binding filter of pVACseq and pVACfuse can now be run with flexible, allele-specific binding-thresholds. This feature can be enabled using the --allele-specific-binding-thresholds flag. The thresholds used are taken from the IEDB recommendations.
  • pVACseq now supports a --pass-only flag that will result in any VCF entries with a FILTER to be skipped. Using this flag, only VCF entries with a FILTER of PASS or . will be processed.
  • We added support for the MHCflurry and MHCnuggets prediction algorithms. These can be used by listing MHCflurry, MHCnuggetsI (for MHC Class I alleles), and/or MHCnuggetsII (for MHC Class II alleles) as the prediction algorithms in your run commands.
  • The default --tdna-vaf and --trna-vaf cutoff values have been updated from 0.4 to 0.25. This is the minimum VAF threshold that an epitope candidate must meet in order to pass the coverage filter.
  • We now offer a graphical user interface, pVACviz, to run pVACseq as an alernative to using the command line. pVACviz, can also be used to plot and filter your pVACseq results.

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


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.