Literature DB >> 33123738

Neoantimon: a multifunctional R package for identification of tumor-specific neoantigens.

Takanori Hasegawa1, Shuto Hayashi2, Eigo Shimizu2, Shinichi Mizuno3, Atsushi Niida1, Rui Yamaguchi2, Satoru Miyano2, Hidewaki Nakagawa4, Seiya Imoto1.   

Abstract

SUMMARY: It is known that some mutant peptides, such as those resulting from missense mutations and frameshift insertions, can bind to the major histocompatibility complex and be presented to antitumor T cells on the surface of a tumor cell. These peptides are termed neoantigen, and it is important to understand this process for cancer immunotherapy. Here, we introduce an R package termed Neoantimon that can predict a list of potential neoantigens from a variety of mutations, which include not only somatic point mutations but insertions, deletions and structural variants. Beyond the existing applications, Neoantimon is capable of attaching and reflecting several additional information, e.g. wild-type binding capability, allele specific RNA expression levels, single nucleotide polymorphism information and combinations of mutations to filter out infeasible peptides as neoantigen.
AVAILABILITY AND IMPLEMENTATION: The R package is available at http://github/hase62/Neoantimon.
© The Author(s) 2020. Published by Oxford University Press.

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Year:  2020        PMID: 33123738      PMCID: PMC7750962          DOI: 10.1093/bioinformatics/btaa616

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

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10.  pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens.

Authors:  Jasreet Hundal; Beatriz M Carreno; Allegra A Petti; Gerald P Linette; Obi L Griffith; Elaine R Mardis; Malachi Griffith
Journal:  Genome Med       Date:  2016-01-29       Impact factor: 11.117

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  4 in total

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3.  Seq2Neo: A Comprehensive Pipeline for Cancer Neoantigen Immunogenicity Prediction.

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4.  Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool.

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