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pVACtools: a computational toolkit to identify and visualize cancer neoantigens

By 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

Posted 19 Dec 2018
bioRxiv DOI: 10.1101/501817 (published DOI: 10.1158/2326-6066.CIR-19-0401)

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. We have developed an in silico sequence analysis toolkit - pVACtools, to facilitate comprehensive neoantigen characterization. pVACtools supports a modular workflow consisting of tools for neoantigen prediction from somatic alterations (pVACseq and pVACfuse), prioritization and selection using a graphical web-based interface (pVACviz) and design of DNA vector-based vaccines (pVACvector) and synthetic long peptide vaccines. pVACtools is available at [pvactools.org][1]. [1]: http://pvactools.org

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