Combining data and knowledge to unravel the genetics of complex traits
Speaker: Alexis Battle, Stanford University, Daphne Koller group
Date: Friday, January 18 2013
Time: 9:00AM to 10:15AM
Refreshments: 8:55AM
Location: Kiva Conference Room, CSAIL 4th floor, 32 Vassar S
Host: Manolis Kellis, MIT
Contact: Manolis Kellis, 617-253-2419, manoli@mit.edu
Recent technological advances have allowed us to collect genomic data
on an unprecedented scale, with the promise of revealing genetic
variants, genes, and pathways disrupted in clinically relevant
phenotypes. However, identifying functional genetic variants and
ultimately unraveling the genetics of complex traits from such data
have presented significant challenges. With millions of genetic
factors to consider, spurious associations and lack of statistical
power are major hurdles, in addition to challenges identifying the
functional role each element plays.
In this talk, I will present two complementary approaches for
improving the analysis of variation in the human genome. First, I
will discuss the direct identification of functional regulatory
variants on a large scale through the use of gene expression as a
high-resolution cellular phenotype. We have sequenced RNA from 922
individuals to provide a direct window into the consequences of
regulatory genetic variation on diverse gene expression phenotypes
including splicing and allelic expression. Second, I will discuss the
use of structured probabilistic models to integrate diverse sources of
data, including genomic annotations and gene network information, into
models of genetic variation in both transcriptional and higher-level
disease traits. These methods significantly improve our power to
identify relevant variants over standard association techniques.
Together, these approaches offer the potential to greatly improve the
identification of functional genetic variants and identify their role
in complex traits and disease risk.
See other events happening in January 2013
