Quantification of population structure using correlated SNPs by shrinkage principal components.

ABSTRACT:

Background/aims

Association studies using unrelated individuals have become the most popular design for mapping complex traits. One of the major challenges of association mapping is avoiding spurious association due to population stratification. Principal component analysis (PCA) on genome-wide marker genotypes is one of the most popular population stratification control methods. It implicitly assumes that the markers are in linkage equilibrium, a condition that is rarely satisfied and that we plan to relax.

Methods

We carefully examined the impact of linkage disequilibrium (LD) on PCA, and proposed a simple modification of the standard PCA to automatically adjust for the correlations among markers.

Results

We demonstrated that LD patterns in genome-wide association d

SUBMITTER: Zou F 

PROVIDER: S-EPMC2912642 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature