Abstract
DATE: |
October 1, 2009 |
TIME: |
1:15 - 3:00 pm |
LOCATION: |
Center for Clinical Sciences Research (CCSR), Rm 4205 |
TITLE: |
Association Studies Involving Rare Variants and Large-Scale DNA Sequence Data |
SPEAKER: |
Nicholas J Schork, PhD |
The growing availability of efficient DNA sequencing technologies is motivating geneticists to leverage these technologies in association studies focused on the identification of genetic variations that influence phenotypic expression and disease susceptibility. However, making sense of DNA sequence data in the context of association studies is problematic. Statistical methods that are appropriate for the analysis of common genetic variations of the type interrogated in contemporary single nucleotide polymorphism (SNP) genotyping chip-based genome-wide association (GWA) studies are not likely to be appropriate for DNA sequence-based association studies, given that rare variations and non-SNP forms of variation must be considered. In fact, the identification and validation of these forms of variation from DNA sequencing runs are themselves problematic and need to be taken into account when analyzed in association studies. In addition, the analysis of rare variations will require genomic annotations (i.e., information about the location of functional elements in the genome) to help put into context their individual and collective biological effects. This talk will outline some general approaches to association analyses involving DNA sequence data, including accommodating coverage information, leveraging local sequence similarity, "collapsing" collections of rare variations to create "genetic meta-factors", exploiting sophisticated in silico methods for sequence annotation, and running sophisticated, very high-dimensional regression and related data mining techniques for association testing purposes.
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