title: Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling.
abstract: Population stratification (PS) represents a major challenge in genome-wide association studies. Using the Genetic Analysis Workshop 16 Problem 1 data, which include samples of rheumatoid arthritis patients and healthy controls, we compared two methods that can be used to evaluate population structure and correct PS in genome-wide association studies: the principal-component analysis method and the multidimensional-scaling method. While both methods identified similar population structures in this dataset, principal-component analysis performed slightly better than the multidimensional-scaling method in correcting for PS in genome-wide association analysis of this dataset.
authors.affiliation: Department of Pharmacogenomics, Johnson & Johnson Pharmaceutical Research and Development, LLC, Raritan, New Jersey 08869 USA. dwang39@its.jnj.com.
authors.forename: Dai
authors.initials: D
authors.lastname: Wang
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
authors.forename: Paul
authors.initials: P
authors.lastname: Stang
authors.forename: Jesse A
authors.initials: JA
authors.lastname: Berlin
authors.forename: Marsha A
authors.initials: MA
authors.lastname: Wilcox
authors.forename: Qingqin
authors.initials: Q
authors.lastname: Li