pVACtools

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

pVACseq

A cancer immunotherapy pipeline for identifying and prioritizing neoantigens from a VCF file.

pVACbind

A cancer immunotherapy pipeline for identifying and prioritizing neoantigens from a FASTA file.

pVACfuse

A tool for detecting neoantigens resulting from gene fusions.

pVACsplice

A tool for detecting neoantigens resulting from splice site variants.

pVACvector

A tool designed to aid specifically in the construction of DNA-based cancer vaccines.

pVACview

An application based on R Shiny that assists users in reviewing, exploring and prioritizing neoantigens from the results of pVACtools processes for personalized cancer vaccine design.

Contents

• pVACseq
  • Features
  • Input File Preparation
  • Getting Started
  • Usage
  • Output Files
  • Filtering Commands
  • Additional Commands
  • Optional Downstream Analysis Tools
  • Common Errors
  • Frequently Asked Questions
• pVACbind
  • Features
  • Prerequisites
  • Getting Started
  • Usage
  • Output Files
  • Filtering Commands
  • Additional Commands
  • Optional Downstream Analysis Tools
• pVACfuse
  • Features
  • Prerequisites
  • Getting Started
  • Usage
  • Output Files
  • Filtering Commands
  • Additional Commands
  • Optional Downstream Analysis Tools
• pVACsplice
  • Features
  • Input File Preparation
  • Getting Started
  • Usage
  • Output Files
  • Filtering Commands
  • Additional Commands
  • Optional Downstream Analysis Tools
• pVACvector
  • Prerequisites
  • Getting Started
  • Usage
  • Additional Commands
  • Output Files
• pVACview
  • Prerequisites
  • pVACseq Module
  • Neofox Module
  • Custom Module
  • Commonly Asked Questions

• Installation
• Courses
• Tools Used By pVACtools
• Frequently Asked Questions
• Release Notes
• License
• Citations
• Funding
• How To Contribute
• Contact
• Mailing List

New in Version 5.2.0

This is a minor feature release. It adds the following features:

• Add a new parameter --percentile-threshold-strategy that controls filtering and tiering behavior when a percentile threshold is set. If this parameter is set to conservative a candidate has to pass both the binding affinity and percentile score thresholds. If it is set to exploratory it only has to pass either the binding affinity or the percentile score threshold. by @ldhtnp in https://github.com/griffithlab/pVACtools/pull/1185

• Add a new parameter --netmhciipan-version that controls which version of NetMHCIIpan and NetMHCIIpanEL are being run. The default remains version 4.1. by @ldhtnp in https://github.com/griffithlab/pVACtools/pull/1181

• The meaning of the Mutation Position column (in the all_epitopes.tsv and filtered.tsv pVACseq reports) and the Pos column (in the aggregated pVACseq report) has been updated to reflect the position(s) in the mutant epitope that are different from the matched wildtype epitope.

  • This is different from the previous behaviors, particular for indels, where previously this column was trying to reflect where the mutation occurred. However, this has proven difficult to programmatically determine correctly for cases with proximal variants, in repetitive regions, or where the mutant amino acid(s) are similar the wildtype amino acid(s).

  • For inframe indels, this change might now result in some positions getting marked as different from the matched wildtype amino acid even though they aren’t technically part of the variant because wildtype amino acids are shifted in relation to the mutant in this type of variants. These shifted amino acids, although not mutated, are now different between mutant and matched wildtype epitope and marked as such. We do believe that this is the better approach because it allows us to evaluate the absolute differences between the matched wildtype and mutant epitopes.

  • These columns are now always NA if the wildtype epitope is NA

  • For making the anchor position evaluation, epitopes with more than two Mutation Position/Pos entries are auto-passed.

It also fixes the following problem(s):

• Fix a bug in the Mutation Position/Pos column where proximal variants and certain inframe indels might result in the incorrect position(s) being identified. As part of this bugfix, the meaning of these columns has been updated (see above.)

• Fix Mutation Position column by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1206

• Fix pVACvector bug that would result in not all junctional epitopes getting tested on clipping. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1200

• Fix a pVACvector bug that would result in an error if the -k flag was not set in a run. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1186

• Fix warning related to new lines in the mouse anchor data files in pVACview. by @ldhtnp in https://github.com/griffithlab/pVACtools/pull/1184

• Fix the column tooltips in pVACview which were previously shifted by a couple of columns. by @ldhtnp in https://github.com/griffithlab/pVACtools/pull/1189

• Fix description of the ref_fasta positional parameter in pvacsplice. by @mhoang22 in https://github.com/griffithlab/pVACtools/pull/1201

• Fix an issue in pVACsplice which would throw an error with non-human transcripts. by @mhoang22 in https://github.com/griffithlab/pVACtools/pull/1198

New in Version 5

This is a major version release. Please note that pVACtools 5.0 is not guaranteed to be backwards-compatible and certain changes could break old workflows.

New Tools

This release adds a new tool, pVACsplice, for prediction neoantigens from splice sites. Please see the full tool documentation for more information. by @mrichters in https://github.com/griffithlab/pVACtools/pull/911

New Features

• This release refactors the pVACvector graph building algorithm in order to increase the probability for finding a solution and reduce the number of iterations needed before a solution is found. Please see the PR describtion for the full details. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1163

• Add a new --aggregate-inclusion-count-limit parameter to set the maximum number of epitopes to include in the metrics.json detailed data for variants that have a large number of candidate neoantigens (e.g., frameshifts). by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1147

• Add a new --biotypes parameter which defines a list of transcript consequence biotypes that the predictions from pVACseq and pVACsplice should be limited to. by @mrichters in https://github.com/griffithlab/pVACtools/pull/911

• Add support for additional alleles that weren’t previously supported, includings ones for dog, mouse, and MHC class II. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1148

Bugfixes

• This relase fixes a bug with the --agregate-inclusion-binding-threshold which would not be used if the --allele-specific-binding-thresholds flag was set. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1147

• The pVACview percentile plots have been updated to include percentiles from elution and immunogenicity algorithms. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1149

• This release fixes a bug where the incorrect neoantigen fasta entry may be used for the reference proteome search if there were multiple variants or alt alleles located at the same genomic position. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1153

• Add additional trailing amino acids for frameshift insertions when creating fasta in order to capture a matched wildtype entry in large repetitive regions. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1155

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.

Citations

Jasreet Hundal , Susanna Kiwala , Joshua McMichael, Chris Miller, Huiming Xia, Alex Wollam, Conner Liu, Sidi Zhao, Yang-Yang Feng, Aaron Graubert, Amber Wollam, Jonas Neichin, Megan Neveau, Jason Walker, William Gillanders, Elaine Mardis, Obi Griffith, Malachi Griffith. pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens. Cancer Immunology Research. 2020 Mar;8(3):409-420. doi: 10.1158/2326-6066.CIR-19-0401. PMID: 31907209.

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.

Huiming Xia, My H. Hoang, Evelyn Schmidt, Susanna Kiwala, Joshua McMichael, Zachary L. Skidmore, Bryan Fisk, Jonathan J. Song, Jasreet Hundal, Thomas Mooney, Jason R. Walker, S. Peter Goedegebuure, Christopher A. Miller, William E. Gillanders, Obi L. Griffith, Malachi Griffith. pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection. Genome Medicine. 2024, 16:132, DOI: 10.1186/s13073-024-01384-7. PMID: 39538339.

Source code

The pVACtools source code is available in GitHub.

License

This project is licensed under BSD 3-Clause Clear License.