 |
 |
SCIENCE AT THE EDGE SEMINAR QB/GEDD Friday, November 1 at 11:30am Room 1400 Biomedical and Physical Sciences Bldg. Refreshments at 11:15 Fei Zou Department of Biostatistics University of North Carolina at chapel Hill Integrated Statistical Analysis of Genome-wide Association Data Genome-wide association studies (GWAS) aim to identify single-nucleotide polymorphisms (SNPs) associated with complex traits. Routinely, first-pass approaches to GWAS data analysis involve association testing for individual SNPs. Attaining significance for any individual SNP test may be difficult due to several factors, including stringent genome-wide testing thresholds and modest genetic effects. Additional challenges are also presented by true biological architectures, including the fact that causal variants may not be genotyped, or that multiple causal variants may be present in a single region, thus diluting the signals. For these situations, regional SNP-set analysis and meta-analysis are commonly used in practice to gain power. In this talk, I'll introduce two regional SNP-set procedures for GWAS and a fast meta-analysis procedure for eQTL studies with related samples, such as twins. In addition, empirical procedures for controlling family-wise errors will be discussed.