pVAC-Seq statistics

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pVAC-Seq specifications

Information


Unique identifier OMICS_11204
Name pVAC-Seq
Alternative name personalized Variant Antigens by Cancer Sequencing
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Elaine Mardis

Publication for personalized Variant Antigens by Cancer Sequencing

pVAC-Seq citations

 (7)
library_books

Population level distribution and putative immunogenicity of cancer neoepitopes

2018
BMC Cancer
PMCID: 5899330
PMID: 29653567
DOI: 10.1186/s12885-018-4325-6

[…] neoepitopes to unrelated peptides, demonstrating that a neoepitope may be more similar to other human, commensal, or pathogenic peptides than its paired normal epitope. This approach also builds upon pVAC-Seq in several significant ways, and could in theory be applied as a post-processing step in any neoantigen prediction pipeline. Although the peptide immune response data we analyzed was limited […]

library_books

Immunopharmacogenomics towards personalized cancer immunotherapy targeting neoantigens

2018
Cancer Sci
PMCID: 5834780
PMID: 29288513
DOI: 10.1111/cas.13498

[…] It is still a major challenge to accurately predict the interaction between neoantigens and immune cells. There are currently several publicly available neoantigen prediction pipelines, including pVAC‐Seq, INTEGRATE‐neo, TSNAD. pVAC‐Seq combines the tumor mutation and expression data to predict neoantigens by invoking NetMHC 3.4; INTEGRATE‐neo was designed to predict neoantigens from fusion ge […]

library_books

Computational Pipeline for the PGV 001 Neoantigen Vaccine Trial

2018
Front Immunol
PMCID: 5778604
PMID: 29403468
DOI: 10.3389/fimmu.2017.01807

[…] another enrolled. The remainder did not enroll due to progression of disease or low-quality tumor samples.Several other groups have released pipelines for neoantigen vaccine prediction, most notably pVAC-seq () and MuPeXI (). A deep comparison between neoantigen pipelines likely requires evaluating T-cell response and antitumor activity after vaccination, which is beyond the scope of this paper. […]

library_books

Neoantigens Generated by Individual Mutations and Their Role in Cancer Immunity and Immunotherapy

2017
Front Immunol
PMCID: 5712389
PMID: 29234329
DOI: 10.3389/fimmu.2017.01679

[…] ipelines that integrate the individual steps were recently developed. Such pipelines for in silico prediction of personalized neoantigens from NGS data with different degrees of functionality include pVAC-seq (), FRED 2 (), INTEGRATE-neo (), and MuPEXI (). However, although an improvement to the use of individual steps, assembling analytical pipelines and executing workflows with a number of conse […]

library_books

Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma

2017
Nat Commun
PMCID: 5701046
PMID: 29170503
DOI: 10.1038/s41467-017-01460-0

[…] les using bwakit (https://github.com/lh3/bwa/tree/master/bwakit) or Omixon Target HLA (Omixon). Potential HLA class I restricted neoantigens were predicted using a custom pipeline comprising modified pVAC-Seq. This early perl based version of pVAC-Seq was not able to generate predictions for indels. NetMHC version 4.0 was used for peptide-MHC affinity predictions; mutated peptides with binding aff […]

library_books

Cancer Immunogenomics: Computational Neoantigen Identification and Vaccine Design

2017
Cold Spring Harb Symp Quant Biol
PMCID: 5702270
PMID: 28389595
DOI: 10.1101/sqb.2016.81.030726

[…] a context-dependent manner ().Because of the complexities of the aforementioned set of steps required to generate predicted neoantigens, our group published a computational pipeline called pVAC-Seq (personalized Variant Antigens by Cancer Sequencing) that is designed to perform these steps in sequence (). pVAC-Seq requires several input data, including an annotated list of somatic variants, compa […]

Citations

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pVAC-Seq institution(s)
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA; Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, USA; Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St. Louis, MO, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA; Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA; Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
pVAC-Seq funding source(s)
The National Human Genome Research Institute (K99 HG007940, NHGRI U54 HG003079); the National Cancer Institute (K22 CA188163, R21 CA179695, R21 CA179695)

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