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.
New in version 1.2¶
This version introduces multithreading to pVACtools. This significantly speeds
up the execution of pVACseq, pVACfuse, and pVACvector. To turn on
multithreading simply set the
--n-threads parameter to the desired number
of threads. This implementation is not CPU-bound. However, when running the
tools using the IEDB RESTful API, we recommend to keep this number small (<5)
as too many parallel calls to their API might lead to IEDB blocking jobs
submitted from your IP address. It is recommended to use a standalone IEDB
installation when running with multiple threads. By default, multithreading is
This version also fixes a few bugs:
- In certain cases pVACvector was not calculating the junction scores correctly, leading to potentially finding a peptide order that would include high-binding junction epitopes or peptide orders that were not optimal. This issue has now been fixed.
- Due to a bug in our packaging code, the 1.1.x versions of pVACtools did not include the latest version of the pVACviz code. This version now includes the most up-to-date version of the graphical user interface.
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.
Jasreet Hundal, Susanna Kiwala, Joshua McMichael, Christopher A Miller, Alexander T Wollam, Huiming Xia, Connor J Liu, Sidi Zhao, Yang-Yang Feng, Aaron P Graubert, Amber Z Wollam, Jonas Neichin, Megan Neveau, Jason Walker, William E Gillanders, Elaine R Mardis, Obi L Griffith, Malachi Griffith. pVACtools: a computational toolkit to select and visualize cancer neoantigens. bioRxiv 501817; doi: https://doi.org/10.1101/501817
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.