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