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Activity Number: 51
Type: Invited
Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
Sponsor: ENAR
Abstract #314448 View Presentation
Title: Bayesian Models for Heterogeneity in Human Cancers
Author(s): Yuan Ji*
Companies: The University of Chicago
Keywords: Feature allocation model ; Indian buffett process ; next-generation sequencing ; somatic mosaicism ; subclone ; tumor heterogeneity

Next-generation sequencing (NGS) data provide a new opportunity to study the genome of various organisms, including that of tumors. We develop Bayesian models based on NGS data to reveal the existence of genome mosaicism, a phenomenon known as having subclones possessing distinct genomes in a tumor sample. Understanding mosaic tumor cells paves ways for the development of precise cancer treatment. We discuss Bayesian models for the inference of local and non-local haplotype variants as evidence of genome mosaicism and tumor heterogeneity. Examples are provided to show the utility of statistical inference with an efficient computational scheme.

Authors who are presenting talks have a * after their name.

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