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Activity Number: 532
Type: Topic Contributed
Date/Time: Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #319310 View Presentation
Title: Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Complex Traits and Improve Signal Prioritization in Genome-Wide Association Studies
Author(s): Qiongshi Lu* and Ryan Powles and Qian Wang and Beixin He and Hongyu Zhao
Companies: Yale University and Yale University and Yale University and Yale New Haven Hospital and Yale University
Keywords: functional annotation ; GWAS ; complex traits ; data integration

Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this work, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS) led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases.

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

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