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Extracting topics from cancer patients' mutational profiles

Image credit: Meetup

Extracting topics from cancer patients' mutational profiles

Abstract

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.

Date
Location
Orange County, California
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Zhi Yang
PhD in Biostatistics