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Open Access 01-12-2009 | Proceedings

Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling

Authors: Dai Wang, Yu Sun, Paul Stang, Jesse A Berlin, Marsha A Wilcox, Qingqin Li

Published in: BMC Proceedings | Special Issue 7/2009

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.

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Title: Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
Authors: Dai Wang
Yu Sun
Paul Stang
Jesse A Berlin
Marsha A Wilcox
Qingqin Li
Publication date: 01-12-2009
Publisher: BioMed Central
Published in: BMC Proceedings / Issue Special Issue 7/2009
Electronic ISSN: 1753-6561
DOI: https://doi.org/10.1186/1753-6561-3-S7-S109

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

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