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Wang Z, et al. Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration. iScience. 2018 Nov 30;1-460. doi: 10.1016/j.isci.2018.10.028.
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Explore transcriptomic deconvolution techniques for cancer research in this comprehensive conference talk. Delve into the methodologies and applications of deconvoluting complex tumor samples with immune infiltration. Learn about estimating tumor cell total mRNA expression across 15 cancer types and its potential for predicting disease progression. Discover the DeMixSC deconvolution framework, which combines single-cell sequencing with benchmark datasets to improve cell-type ratio analysis in heterogeneous tissue samples. Gain insights from related research papers and understand how these advanced techniques contribute to a deeper understanding of cancer biology and potential therapeutic approaches.

A Guide to Perform Transcriptomic Deconvolution in Cancer

Computational Genomics Summer Institute CGSI
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