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 5.3.0

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

• Identify junctions included in final vector design in the junctions.tsv. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1216

• Prevent Excel export in pVACview from creating extra title header row. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1227

It also fixes the following problem(s):

• Ensure export in pVACview maintains the Index column. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1213

• Enable auto-combination of DP and DQ alpha and beta chains in pVACsplice. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1219

• Handle pVACsplice generate_protein_fasta cases where mutant sequence contains no epitopes different from wildtype. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1226

• Support pVACsplice regtools/gtf input data with missing transcript_version field. by @mhoang22 in https://github.com/griffithlab/pVACtools/pull/1224

• Ensure that the directory names generated when removing peptides in pVACvector graph don’t contain “/”. by @susannasiebert in https://github.com/griffithlab/pVACtools/pull/1218

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.