American Statistical Association
The last three years have seen great successes in Genome-Wide Association Studies (GWAS) which have identified numerous genetic variants underlying complex traits. The analysis and interpretation of data from GWAS presents great statistical and computational challenges, especially after the initial discoveries of variants carrying relatively large effects. Although various statistical approaches have been or are being developed to better analyze GWAS data, it has become apparent that the incorporation of information from prior studies and other sources is indispensable. In this presentation, we discuss our recently developed statistical methods and bioinformatics tools that are designed to more effectively integrate diverse types of prior biological information in analyzing GWAS data. The usefulness of these methods will be illustrated through their applications to some recent large-scale GWAS data.
|Date:||Wednesday, October 1, 2008|
|Time:||4:00 P.M. - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.