Robust Method for Correcting Population Stratification in Genome-Wide Association Studies

• Activity Number: 515
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Li Liu*+ and Donghui Zhang
• Companies: sanofi-aventis and sanofi-aventis
• Keywords: population stratification ; genome-wide association study ; Robust SVD

Abstract

Population stratification refers to allele frequency differences between cases and controls due to systematic ancestry differences. Correcting for population stratification is very important in genome-wide association studies since population stratification can cause spurious associations in disease studies. Price et al (2006) proposed to deal with stratification using PCA. This approach can be easily applied to thousands of markers, and the correction is specific to a marker's variation in frequency across ancestral populations. This approach has proven useful in many situations. However, it cannot handle missing values and outliers. We propose to use robust singular value decomposition to deal with population stratification, which can handle missing values and outliers, so we do not need complex missing value imputation and outlier detection before the analysis.