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Bioinformatics. 2017 Feb 15;33(4):555-557. doi: 10.1093/bioinformatics/btw674.

INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery.

Zhang J1,2,3, Mardis ER1,3,4,5,6, Maher CA1,2,3,7.

Author information

1
McDonnell Genome Institute.
2
Department of Internal Medicine.
3
Siteman Cancer Center.
4
Department of Molecular Microbiology.
5
Department of Medicine.
6
Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
7
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63105, USA.

Abstract

Motivation:

While high-throughput sequencing (HTS) has been used successfully to discover tumor-specific mutant peptides (neoantigens) from somatic missense mutations, the field currently lacks a method for identifying which gene fusions may generate neoantigens.

Results:

We demonstrate the application of our gene fusion neoantigen discovery pipeline, called INTEGRATE-Neo, by identifying gene fusions in prostate cancers that may produce neoantigens.

Availability and Implementation:

INTEGRATE-Neo is implemented in C ++ and Python. Full source code and installation instructions are freely available from https://github.com/ChrisMaherLab/INTEGRATE-Neo .

Contact:

christophermaher@wustl.edu.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
27797777
PMCID:
PMC5408800
DOI:
10.1093/bioinformatics/btw674
[Indexed for MEDLINE]
Free PMC Article

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