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Interrogating population structure and its impact on association tests

We found from our analysis of the Genetic Analysis Workshop 17 data that the population structure of the 697 unrelated individuals was an important confounding factor for association studies, even if it was not explicitly considered when simulating the phenotypes. We uncovered structures beyond the...

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Detalles Bibliográficos
Autores principales: Qin, Huaizhen, Elston, Robert C, Zhu, Xiaofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287860/
https://www.ncbi.nlm.nih.gov/pubmed/22373290
http://dx.doi.org/10.1186/1753-6561-5-S9-S25
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author Qin, Huaizhen
Elston, Robert C
Zhu, Xiaofeng
author_facet Qin, Huaizhen
Elston, Robert C
Zhu, Xiaofeng
author_sort Qin, Huaizhen
collection PubMed
description We found from our analysis of the Genetic Analysis Workshop 17 data that the population structure of the 697 unrelated individuals was an important confounding factor for association studies, even if it was not explicitly considered when simulating the phenotypes. We uncovered structures beyond the reported ethnicities and found ample evidence of phenotype–population structure associations. The first 10 principal components of the genotype data of the 697 individuals demonstrated much stronger associations with Q1, Q2, and the disease than did the individuals’ ethnicities. In addition, we observed that population structure was a confounding factor for the Q1-gene association when identifying the significant genes both with and without adjusting for the causal single-nucleotide polymorphisms, the ethnicities, and the principal components. Many false discoveries remained after adjusting for the causal single-nucleotide polymorphisms. Adjusting for the principal components appeared more effective than did adjusting for ethnicity in terms of preventing false discoveries. This analysis was performed with knowledge of the causal loci.
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spelling pubmed-32878602012-02-28 Interrogating population structure and its impact on association tests Qin, Huaizhen Elston, Robert C Zhu, Xiaofeng BMC Proc Proceedings We found from our analysis of the Genetic Analysis Workshop 17 data that the population structure of the 697 unrelated individuals was an important confounding factor for association studies, even if it was not explicitly considered when simulating the phenotypes. We uncovered structures beyond the reported ethnicities and found ample evidence of phenotype–population structure associations. The first 10 principal components of the genotype data of the 697 individuals demonstrated much stronger associations with Q1, Q2, and the disease than did the individuals’ ethnicities. In addition, we observed that population structure was a confounding factor for the Q1-gene association when identifying the significant genes both with and without adjusting for the causal single-nucleotide polymorphisms, the ethnicities, and the principal components. Many false discoveries remained after adjusting for the causal single-nucleotide polymorphisms. Adjusting for the principal components appeared more effective than did adjusting for ethnicity in terms of preventing false discoveries. This analysis was performed with knowledge of the causal loci. BioMed Central 2011-11-29 /pmc/articles/PMC3287860/ /pubmed/22373290 http://dx.doi.org/10.1186/1753-6561-5-S9-S25 Text en Copyright ©2011 Qin 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
Qin, Huaizhen
Elston, Robert C
Zhu, Xiaofeng
Interrogating population structure and its impact on association tests
title Interrogating population structure and its impact on association tests
title_full Interrogating population structure and its impact on association tests
title_fullStr Interrogating population structure and its impact on association tests
title_full_unstemmed Interrogating population structure and its impact on association tests
title_short Interrogating population structure and its impact on association tests
title_sort interrogating population structure and its impact on association tests
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287860/
https://www.ncbi.nlm.nih.gov/pubmed/22373290
http://dx.doi.org/10.1186/1753-6561-5-S9-S25
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