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

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 structur...

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Detalles Bibliográficos
Autores principales: Wang, Dai, Sun, Yu, Stang, Paul, Berlin, Jesse A, Wilcox, Marsha A, Li, Qingqin
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795880/
https://www.ncbi.nlm.nih.gov/pubmed/20017973
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author Wang, Dai
Sun, Yu
Stang, Paul
Berlin, Jesse A
Wilcox, Marsha A
Li, Qingqin
author_facet Wang, Dai
Sun, Yu
Stang, Paul
Berlin, Jesse A
Wilcox, Marsha A
Li, Qingqin
author_sort Wang, Dai
collection PubMed
description 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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spelling pubmed-27958802009-12-18 Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling Wang, Dai Sun, Yu Stang, Paul Berlin, Jesse A Wilcox, Marsha A Li, Qingqin BMC Proc Proceedings 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. BioMed Central 2009-12-15 /pmc/articles/PMC2795880/ /pubmed/20017973 Text en Copyright ©2009 Wang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Wang, Dai
Sun, Yu
Stang, Paul
Berlin, Jesse A
Wilcox, Marsha A
Li, Qingqin
Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title_full Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title_fullStr Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title_full_unstemmed Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title_short Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
title_sort comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795880/
https://www.ncbi.nlm.nih.gov/pubmed/20017973
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