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.

pVACtools immunotherapy workflow

Contents

New in Version 6.1.1

This is a bugfix release. It fixes the following problem(s):

New in Version 6

This is a major version release. Please note that pVACtools 6.0 is not guaranteed to be backwards-compatible and certain changes could break old workflows. It also removes support for Python 3.7 and 3.8.

New Tools

  • A new tool, pVACcompare allows users to visualize differences between output files from different pVACtools versions. This tool may be useful when investigating changes to predicted neoantigens between versions in controlled experiments where enumerating and explaning such differences may be crucial, e.g. in clinical trials. The tool can be run using the pvactools compare command. For more information please see the Comparison Tool documentation.

  • A new standalone command pvacseq create_peptide_ordering_form generates peptide ordering files (FASTA, annotated ordering Excel spreadsheet, and review template Excel spreadsheet) to streamline preparation of peptides for synthesis and review. For more information please see the documentation

New Features

  • pVACseq and pVACsplice now take into account the MANE Select and Canonical status of a transcript for filtering, prioritizing, and tiering a neoantigen candidate. MANE Select, Canonical, and TSL status is evaluated according to the new --transcript-prioritization-strategy parameter. This parameter allows users to list one or more critieria (mane_select, canonical, tsl) to take into consideration. As part of this update the “transcript support level filter” has been renamed to “transcript filter” including the standalone command which is now pvacseq|pvacsplice transcript_filer instead of pvacseq|pvacsplice transcript_support_level_filter.

  • The aggregate report tiers have been updated to add four new tier:

    • PoorBinder: candidate fails the binding criteria but passes all other critieria.

    • RefMatch: candidate has a reference match but passes all other criteria.

    • ProbPos: candidate has a problematic amino acid but passes all other criteria.

    • PoorTranscript: a candidate’s best transcript is neither MANE Select, Canonical, nor meets the TSL cutoff (depending on the specified transcript-prioritization-strategy; only available in pVACseq and pVACsplice).

  • A new set of standalone commands, pvacseq|fuse|splice|bind update_tiers, has been added to update the tiering in an aggregate report if different tiering thresholds are desired after the initial pipeline run.

  • By default, transcripts where the FLAGS VEP annotation is set will now be filtered out before processing by pVACseq and pVACsplice. This field identifies transcripts where the CDS 5’ or 3’ is incomplete. A new parameter --allow-incomplete-transcripts has been added which can be used to replicate the previous behavior where such transcripts were included.

  • The pVACsplice logic for aggregating variants in the aggregate report creation has been updated to aggregate neoantigen candidates from the same Junction together instead of using the Index.

  • Output file names of the reports have been updated to include MHC_I/MHC_II/Combined prefixes for easier identification of the type of output file.

Bugfixes

  • This relase fixes a bug with sorting of pVACfuse output files.

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.