Seminar at SMU Delhi
March 15, 2012 (Thursday) ,
3:30 PM at Webinar
Speaker:
Samsiddhi Bhattacharya,
National Institute of Biomedical Genomics
Title:
Statistical Methods for Discovering Pleiotropic Genetic Variants
Abstract of Talk
Pleiotropy is defined as the phenomenon where a single gene (or locus) controls multiple external
traits. Many traits and diseases are thought to be closely related and probably modulated by common
underlying pathways. Taking advantage of these relationships, multiple genome-wide association
studies (GWAS) of different phenotypes can be combined (e.g. meta-analysis). This approach gives a
promising new direction to detect pleiotropic loci having small effects undetected through individual
GWAS. It also helps better understand the shared etiology between traits. Pooling GWAS increases
power, but also poses methodological challenges due to heterogeneity. We propose a flexible ‘subset-
based approach’ that explores all possible subsets of traits for the presence of true association signals,
in the same direction or in opposite directions, and then evaluates the significance of the signal
accounting for subset-search. An efficient analytical approach for p-value estimation will be discussed
and simulation-based power comparisons with other meta-analysis approaches will be shown.