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Comparison of false-discovery rate for genome-wide and fine mapping regions

With technological advances in high-throughput genotyping, it is not unusual to perform hundreds of thousands of tests for each phenotype. Thus, correction to control type I error is essential. The false-discovery rate (FDR) has been successfully used in genome-wide expression data. However, its per...

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Detalles Bibliográficos
Autores principales: Tabangin, Meredith E, Woo, Jessica G, Liu, Chunyan, Nick, Todd G, Martin, Lisa J
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367535/
https://www.ncbi.nlm.nih.gov/pubmed/18466492
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author Tabangin, Meredith E
Woo, Jessica G
Liu, Chunyan
Nick, Todd G
Martin, Lisa J
author_facet Tabangin, Meredith E
Woo, Jessica G
Liu, Chunyan
Nick, Todd G
Martin, Lisa J
author_sort Tabangin, Meredith E
collection PubMed
description With technological advances in high-throughput genotyping, it is not unusual to perform hundreds of thousands of tests for each phenotype. Thus, correction to control type I error is essential. The false-discovery rate (FDR) has been successfully used in genome-wide expression data. However, its performance has not been evaluated for association analysis. Our objective was to analyze the Genetic Analysis Workshop 15 simulated data set, with answers, to evaluate FDR for genome-wide association and fine mapping. In genome-wide analysis, FDR performed well, with good localization of positive results. However, in fine mapping, all tested methods performed poorly, producing a high proportion of significant results. Thus, caution should be used when employing FDR for fine mapping.
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spelling pubmed-23675352008-05-06 Comparison of false-discovery rate for genome-wide and fine mapping regions Tabangin, Meredith E Woo, Jessica G Liu, Chunyan Nick, Todd G Martin, Lisa J BMC Proc Proceedings With technological advances in high-throughput genotyping, it is not unusual to perform hundreds of thousands of tests for each phenotype. Thus, correction to control type I error is essential. The false-discovery rate (FDR) has been successfully used in genome-wide expression data. However, its performance has not been evaluated for association analysis. Our objective was to analyze the Genetic Analysis Workshop 15 simulated data set, with answers, to evaluate FDR for genome-wide association and fine mapping. In genome-wide analysis, FDR performed well, with good localization of positive results. However, in fine mapping, all tested methods performed poorly, producing a high proportion of significant results. Thus, caution should be used when employing FDR for fine mapping. BioMed Central 2007-12-18 /pmc/articles/PMC2367535/ /pubmed/18466492 Text en Copyright © 2007 Tabangin 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
Tabangin, Meredith E
Woo, Jessica G
Liu, Chunyan
Nick, Todd G
Martin, Lisa J
Comparison of false-discovery rate for genome-wide and fine mapping regions
title Comparison of false-discovery rate for genome-wide and fine mapping regions
title_full Comparison of false-discovery rate for genome-wide and fine mapping regions
title_fullStr Comparison of false-discovery rate for genome-wide and fine mapping regions
title_full_unstemmed Comparison of false-discovery rate for genome-wide and fine mapping regions
title_short Comparison of false-discovery rate for genome-wide and fine mapping regions
title_sort comparison of false-discovery rate for genome-wide and fine mapping regions
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367535/
https://www.ncbi.nlm.nih.gov/pubmed/18466492
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