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Activity Number: 5
Type: Invited
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract #314394
Title: Uncovering Genetic Architecture for Complex Diseases from Integrated Functional Genomics Analysis
Author(s): Hongyu Zhao* and Dongjun Chung and Can Yang and Cong Li and Qian Wang and Joel Gelernter
Companies: Yale School of Public Health and Medical University of South Carolina and Hong Kong Baptist University and Yale University and Yale University and Yale School of Medicine
Keywords: statistical genetics ; genomics ; genome wide association studies ; bioinformatics ; computational biology ; data integration
Abstract:

Genome-Wide Association Studies (GWAS) in the past 10 years have led to the identifications of thousands of genetic variants associated with hundreds of human diseases. Although successful, the results from GWAS suggest that most complex traits (e.g. cancer, schizophrenia, diabetes) are likely affected by many hundreds or even thousands of genetic variants in the human genome, so the majority of disease associated variants with relatively small effects have not been identified yet. To improve statistical power, various approaches have been proposed to jointly analyze GWAS data across multiple phenotypes in combination of rich functional annotations for the human genome to identify additional disease associated variants. In this presentation, we will first introduce different types of data and their informativeness on implicating disease associated variants, and then discuss statistical methods that can help better delineate the genetic architecture underlying various complex diseases. This is joint work with Dongjun Chung, Can Yang, Cong Li, Qian Wang, and Joel Gelernter.


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

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