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Activity Number:
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594
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
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Sponsor:
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International Chinese Statistical Association
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Abstract #319274
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Title:
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Epigenome Isoform Analysis with Applications
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Author(s):
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Hongkai Ji* and Weixiang Fang
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Companies:
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Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Bloomberg School of Public Health
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Keywords:
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Genomics ;
Epigenomics ;
High-throughput sequencing ;
Big data ;
Bayesian statistics ;
Data integration
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Abstract:
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Epigenome is a crucial component for understating gene regulation. The massive amounts of data generated by the Roadmap Epigenomics project create an opportunity to study the coordination of different types of epigenomic signals from different cis-regulatory elements. Here we develop Epigenome Isoform Analysis (EIA) to systematically discover and analyze such coordination patterns using a hierarchical latent mixture model. We show that cis-regulatory element isoforms discovered by EIA provides a concise but biologically meaningful description of the highly complex epigenome landscape. We demonstrate its use in analyzing epigenomic changes between different biological conditions.
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Authors who are presenting talks have a * after their name.
