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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.
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

.. toctree::
   :maxdepth: 2

   pvacseq
   pvacbind
   pvacfuse
   pvacvector
   pvacview


.. toctree::
   :maxdepth: 1

   install
   courses
   tools
   frequently_asked_questions
   releases
   license
   citation
   funding
   contribute
   contact
   mailing_list

New in Release |release|

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

  • Previously, pVACview would add an additional header line to Excel spreadsheets when exporting a TSV. This has been fixed so that the first line in the spreadsheet is the actual header line. by @susannasiebert in #1143
  • One of the pVACview figures used to describe various anchor scenarios has been updated so that the ordering of the scenarios is consistent with other figures and descriptions throughout. Screenshots and documentation has been updated appropriately. by @susannasiebert in #1144
  • The class II pVACview demo data was out-of-date and not reflecting recent updates to the HLA alpha-beta chain handling. This file has now been updated. by @susannasiebert in #1145

Past release notes can be found on our :ref:`releases` page.

To stay up-to-date on the latest pVACtools releases please join our :ref:`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.

Source code

The pVACtools source code is available in GitHub.

License

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