Abstract
Tumor neoantigens are at the core of immunological tumor control and response to immunotherapy. In silico prediction of tumor neoantigens from next-generation sequencing (NGS) data is possible but requires the assembly of complex, multistep computational pipelines and extensive data preprocessing. Using public data from two cancer cell lines, here we show how TIminer, a framework to perform immunogenomics analyses, can be easily used to assemble and run customized pipelines to predict cancer neoantigens from multisample NGS data.
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