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Titlebook: Bioinformatics for Cancer Immunotherapy; Methods and Protocol Sebastian Boegel Book 2020 Springer Science+Business Media, LLC, part of Spri

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https://doi.org/10.1007/978-3-642-93460-5sing 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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SomaticSeq: An Ensemble and Machine Learning Method to Detect Somatic Mutations, just the coding regions), the number of sequencing errors easily outnumbers the number of real somatic mutations by orders of magnitudes. Here, we describe SomaticSeq, which incorporates multiple somatic mutation detection algorithms and then uses machine learning to vastly improve the accuracy of the somatic mutation call sets.
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Identification of Epitope-Specific T Cells in T-Cell Receptor Repertoires,itate the study of T-cell epitope specificity, we developed a prediction tool, TCRex, that can identify epitope-specific T-cell receptors (TCRs) directly from TCR repertoire data and perform epitope-specificity enrichment analyses. This chapter details the use of the TCRex web tool.
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The Clinical Potential of NMR Imaging,ighly accurate HLA typing solution, arcasHLA. We provide a detailed outline for practitioners using our protocol to perform HLA typing and demonstrate the applicability of arcasHLA in several clinical samples from tumors.
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