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An integrated genome-wide association analysis on rheumatoid arthritis data

We propose a nonparametric association analysis combining both family and unrelated case-control genotype data. Under the assumption of Hardy-Weinberg equilibrium, we formed an affected group to compare with a group of unaffecteds. Comparison with traditional case-control chi-square test and transmi...

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Detalles Bibliográficos
Autores principales: Zhang, Jun, Zhu, Xiaofeng, Cooper, Richard S
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367523/
https://www.ncbi.nlm.nih.gov/pubmed/18466533
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author Zhang, Jun
Zhu, Xiaofeng
Cooper, Richard S
author_facet Zhang, Jun
Zhu, Xiaofeng
Cooper, Richard S
author_sort Zhang, Jun
collection PubMed
description We propose a nonparametric association analysis combining both family and unrelated case-control genotype data. Under the assumption of Hardy-Weinberg equilibrium, we formed an affected group to compare with a group of unaffecteds. Comparison with traditional case-control chi-square test and transmission-disequilibrium test shows that this new approach has noticeably improved power. All analysis was based on the simulated rheumatoid arthritis data provided by Genetic Analysis Workshop 15. In the situation of population stratification, we also suggest an approach to update the genotype data using principal components. However, the Genetic Analysis Workshop 15 simulation data does not simulate population stratification. All analysis was done without knowledge of the answers.
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spelling pubmed-23675232008-05-06 An integrated genome-wide association analysis on rheumatoid arthritis data Zhang, Jun Zhu, Xiaofeng Cooper, Richard S BMC Proc Proceedings We propose a nonparametric association analysis combining both family and unrelated case-control genotype data. Under the assumption of Hardy-Weinberg equilibrium, we formed an affected group to compare with a group of unaffecteds. Comparison with traditional case-control chi-square test and transmission-disequilibrium test shows that this new approach has noticeably improved power. All analysis was based on the simulated rheumatoid arthritis data provided by Genetic Analysis Workshop 15. In the situation of population stratification, we also suggest an approach to update the genotype data using principal components. However, the Genetic Analysis Workshop 15 simulation data does not simulate population stratification. All analysis was done without knowledge of the answers. BioMed Central 2007-12-18 /pmc/articles/PMC2367523/ /pubmed/18466533 Text en Copyright © 2007 Zhang 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
Zhang, Jun
Zhu, Xiaofeng
Cooper, Richard S
An integrated genome-wide association analysis on rheumatoid arthritis data
title An integrated genome-wide association analysis on rheumatoid arthritis data
title_full An integrated genome-wide association analysis on rheumatoid arthritis data
title_fullStr An integrated genome-wide association analysis on rheumatoid arthritis data
title_full_unstemmed An integrated genome-wide association analysis on rheumatoid arthritis data
title_short An integrated genome-wide association analysis on rheumatoid arthritis data
title_sort integrated genome-wide association analysis on rheumatoid arthritis data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367523/
https://www.ncbi.nlm.nih.gov/pubmed/18466533
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