pVACtools: a computational toolkit to select and visualize cancer neoantigens

Hundal, J.; Kiwala, S.; McMichael, J.; Miller, C. A.; Wollam, A. T.; Xia, H.; Liu, C. J.; Zhao, S.; Feng, Y.-Y.; Graubert, A. P.; Wollam, A. Z.; Neichin, J.; Neveau, M.; Walker, J.; Gillanders, W. E.; Mardis, E. R.; Griffith, O. L.; Griffith, M.

doi:10.1101/501817

bioRxiv · 10.1101/501817

pVACtools: a computational toolkit to select and visualize cancer neoantigens

Hundal, J.·Kiwala, S.·McMichael, J.·Miller, C. A.·Wollam, A. T.·Xia, H.·Liu, C. J.·Zhao, S.·Feng, Y.-Y.·Graubert, A. P.·Wollam, A. Z.·Neichin, J.·Neveau, M.·Walker, J.·Gillanders, W. E.·Mardis, E. R.·Griffith, O. L.·Griffith, M.

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Abstract

The elucidation 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 method - pVACtools, to facilitate comprehensive neoantigen characterization. This modular workflow consists of tools for neoantigen prediction from somatic alterations (pVACseq and pVACfuse), prioritization and selection using a graphical web-based interface (pVACviz), and determining the optimal order of neoantigen candidates in a DNA vector-based vaccine(pVACvector).

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Hundal, J., Kiwala, S., McMichael, J., Miller, C. A., Wollam, A. T., Xia, H., Liu, C. J., Zhao, S., Feng, Y.-Y., Graubert, A. P., Wollam, A. Z., Neichin, J., Neveau, M., Walker, J., Gillanders, W. E., Mardis, E. R., Griffith, O. L., Griffith, M.. 2018-12-19. pVACtools: a computational toolkit to select and visualize cancer neoantigens. https://doi.org/10.1101/501817

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