Zhang Jin, Mardis Elaine R, Maher Christopher A
McDonnell Genome Institute.
Department of Internal Medicine.
Bioinformatics. 2017 Feb 15;33(4):555-557. doi: 10.1093/bioinformatics/btw674.
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.
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.
INTEGRATE-Neo is implemented in C ++ and Python. Full source code and installation instructions are freely available from https://github.com/ChrisMaherLab/INTEGRATE-Neo .
Supplementary data are available at Bioinformatics online.
虽然高通量测序（HTS）已成功用于从体细胞错义突变中发现肿瘤特异性突变肽（新抗原），但该领域目前缺乏一种鉴定哪些基因融合可能产生新抗原的方法。
我们通过鉴定前列腺癌中可能产生新抗原的基因融合，展示了我们名为INTEGRATE-Neo的基因融合新抗原发现流程的应用。
INTEGRATE-Neo用C++和Python实现。完整的源代码和安装说明可从https://github.com/ChrisMaherLab/INTEGRATE-Neo免费获取。
补充数据可在《生物信息学》在线获取。
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