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Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study
Genome-wide association studies (GWAS) have been successful in identifying loci associated with a wide range of complex human traits and diseases. Up to now, the majority of GWAS have focused on European populations. However, the inclusion of other ethnic groups as well as admixed populations in GWA...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385148/ https://www.ncbi.nlm.nih.gov/pubmed/25762173 http://dx.doi.org/10.1007/s10654-015-9998-4 |
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author | Medina-Gomez, Carolina Felix, Janine Frédérique Estrada, Karol Peters, Marjoline Josephine Herrera, Lizbeth Kruithof, Claudia Jeanette Duijts, Liesbeth Hofman, Albert van Duijn, Cornelia Marja Uitterlinden, Andreas Gerardus Jaddoe, Vincent Wilfred Vishal Rivadeneira, Fernando |
author_facet | Medina-Gomez, Carolina Felix, Janine Frédérique Estrada, Karol Peters, Marjoline Josephine Herrera, Lizbeth Kruithof, Claudia Jeanette Duijts, Liesbeth Hofman, Albert van Duijn, Cornelia Marja Uitterlinden, Andreas Gerardus Jaddoe, Vincent Wilfred Vishal Rivadeneira, Fernando |
author_sort | Medina-Gomez, Carolina |
collection | PubMed |
description | Genome-wide association studies (GWAS) have been successful in identifying loci associated with a wide range of complex human traits and diseases. Up to now, the majority of GWAS have focused on European populations. However, the inclusion of other ethnic groups as well as admixed populations in GWAS studies is rapidly rising following the pressing need to extrapolate findings to non-European populations and to increase statistical power. In this paper, we describe the methodological steps surrounding genetic data generation, quality control, study design and analytical procedures needed to run GWAS in the multiethnic and highly admixed Generation R Study, a large prospective birth cohort in Rotterdam, the Netherlands. Furthermore, we highlight a number of practical considerations and alternatives pertinent to the quality control and analysis of admixed GWAS data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10654-015-9998-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4385148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-43851482015-04-08 Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study Medina-Gomez, Carolina Felix, Janine Frédérique Estrada, Karol Peters, Marjoline Josephine Herrera, Lizbeth Kruithof, Claudia Jeanette Duijts, Liesbeth Hofman, Albert van Duijn, Cornelia Marja Uitterlinden, Andreas Gerardus Jaddoe, Vincent Wilfred Vishal Rivadeneira, Fernando Eur J Epidemiol Genetic Epidemiology Genome-wide association studies (GWAS) have been successful in identifying loci associated with a wide range of complex human traits and diseases. Up to now, the majority of GWAS have focused on European populations. However, the inclusion of other ethnic groups as well as admixed populations in GWAS studies is rapidly rising following the pressing need to extrapolate findings to non-European populations and to increase statistical power. In this paper, we describe the methodological steps surrounding genetic data generation, quality control, study design and analytical procedures needed to run GWAS in the multiethnic and highly admixed Generation R Study, a large prospective birth cohort in Rotterdam, the Netherlands. Furthermore, we highlight a number of practical considerations and alternatives pertinent to the quality control and analysis of admixed GWAS data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10654-015-9998-4) contains supplementary material, which is available to authorized users. Springer Netherlands 2015-03-12 2015 /pmc/articles/PMC4385148/ /pubmed/25762173 http://dx.doi.org/10.1007/s10654-015-9998-4 Text en © The Author(s) 2015 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Genetic Epidemiology Medina-Gomez, Carolina Felix, Janine Frédérique Estrada, Karol Peters, Marjoline Josephine Herrera, Lizbeth Kruithof, Claudia Jeanette Duijts, Liesbeth Hofman, Albert van Duijn, Cornelia Marja Uitterlinden, Andreas Gerardus Jaddoe, Vincent Wilfred Vishal Rivadeneira, Fernando Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title | Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title_full | Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title_fullStr | Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title_full_unstemmed | Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title_short | Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study |
title_sort | challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the generation r study |
topic | Genetic Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385148/ https://www.ncbi.nlm.nih.gov/pubmed/25762173 http://dx.doi.org/10.1007/s10654-015-9998-4 |
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