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

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

Jin Zhang  1   2   3 , Elaine R Mardis  1   3   4   5   6 , Christopher A Maher  1   2   3   7
Affiliations

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

Jin Zhang et al. Bioinformatics. .

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.

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Figures

Fig. 1.
Fig. 1.
Overview of INTEGRATE-Neo. Green box is data, and blue box is a module
See this image and copyright information in PMC

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