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2019-07-30_extracting_topics_from_cancer_patients_mutational_profiles/Links.txt
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Topic modeling in cancer patients' mutational profiles | ||
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https://lda-mutations.netlify.com/#1 | ||
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https://github.com/zhiiiyang |
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2019-07-30_extracting_topics_from_cancer_patients_mutational_profiles/README.md
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# Topic modeling in cancer patients' mutational profiles | ||
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* 2019-07-30 | ||
* Speaker: Zhi Yang | ||
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## Abstract | ||
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Topic models allow us to access the contribution of each topic and its | ||
representations across different documents. Human genomes have been | ||
exposed to an assortment of mutational processes by contributing to | ||
unique patterns of somatic mutations. What would happen if we apply | ||
the same concept to the somatic mutations obtained from the cancer | ||
patients and look for “topics” of mutations? I will introduce a simple | ||
example of Latent Dirichlet Allocation (LDA) and its application in | ||
investigating cancer patients' mutational profiles in addition to | ||
available Bayesian tools in R to conduct statistical inference. |
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