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Treating phenotype as given: a simple resampling method for genome-wide association studies

Significance of genetic association to a marker has been traditionally evaluated through statistics that are standardized such that their null distributions conform to some known ones. Distributional assumptions are often required in this standardization procedure. Based on the observation that the...

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Detalles Bibliográficos
Autores principales: Wang, Kai, Huang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287899/
https://www.ncbi.nlm.nih.gov/pubmed/22373312
http://dx.doi.org/10.1186/1753-6561-5-S9-S60
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author Wang, Kai
Huang, Jian
author_facet Wang, Kai
Huang, Jian
author_sort Wang, Kai
collection PubMed
description Significance of genetic association to a marker has been traditionally evaluated through statistics that are standardized such that their null distributions conform to some known ones. Distributional assumptions are often required in this standardization procedure. Based on the observation that the phenotype remains the same regardless of the marker being investigated, we propose a simple statistic that does not need such standardization. We propose a resampling procedure to assess this statistic’s genome-wide significance. This method has been applied to replicate 2 of the Genetic Analysis Workshop 17 simulated data on unrelated individuals in an attempt to map phenotype Q2. However, none of the selected SNPs are in genes that are disease-causing. This may be due to the weak effect that each genetic factor has on Q2.
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spelling pubmed-32878992012-02-28 Treating phenotype as given: a simple resampling method for genome-wide association studies Wang, Kai Huang, Jian BMC Proc Proceedings Significance of genetic association to a marker has been traditionally evaluated through statistics that are standardized such that their null distributions conform to some known ones. Distributional assumptions are often required in this standardization procedure. Based on the observation that the phenotype remains the same regardless of the marker being investigated, we propose a simple statistic that does not need such standardization. We propose a resampling procedure to assess this statistic’s genome-wide significance. This method has been applied to replicate 2 of the Genetic Analysis Workshop 17 simulated data on unrelated individuals in an attempt to map phenotype Q2. However, none of the selected SNPs are in genes that are disease-causing. This may be due to the weak effect that each genetic factor has on Q2. BioMed Central 2011-11-29 /pmc/articles/PMC3287899/ /pubmed/22373312 http://dx.doi.org/10.1186/1753-6561-5-S9-S60 Text en Copyright ©2011 Wang and Huang; 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, Kai
Huang, Jian
Treating phenotype as given: a simple resampling method for genome-wide association studies
title Treating phenotype as given: a simple resampling method for genome-wide association studies
title_full Treating phenotype as given: a simple resampling method for genome-wide association studies
title_fullStr Treating phenotype as given: a simple resampling method for genome-wide association studies
title_full_unstemmed Treating phenotype as given: a simple resampling method for genome-wide association studies
title_short Treating phenotype as given: a simple resampling method for genome-wide association studies
title_sort treating phenotype as given: a simple resampling method for genome-wide association studies
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287899/
https://www.ncbi.nlm.nih.gov/pubmed/22373312
http://dx.doi.org/10.1186/1753-6561-5-S9-S60
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