Abstract
Summary: Recently, a number of powerful computational tools for dissecting tumor-immune cell interactions from next-generation sequencing data have been developed. However, the assembly of analytical pipelines and execution of multi-step workflows are laborious and involve a large number of intermediate steps with many dependencies and parameter settings. Here we present TIminer, an easy-to-use computational pipeline for mining tumor-immune cell interactions from next-generation sequencing data. TIminer enables integrative immunogenomic analyses, including: human leukocyte antigens typing, neoantigen prediction, characterization of immune infiltrates and quantification of tumor immunogenicity.
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CITATION STYLE
Tappeiner, E., Finotello, F., Charoentong, P., Mayer, C., Rieder, D., & Trajanoski, Z. (2017). TIminer: NGS data mining pipeline for cancer immunology and immunotherapy. Bioinformatics, 33(19), 3140–3141. https://doi.org/10.1093/bioinformatics/btx377
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