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Testing allele homogeneity: the problem of nested hypotheses

BACKGROUND: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic...

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Autores principales: Izbicki, Rafael, Fossaluza, Victor, Hounie, Ana Gabriela, Nakano, Eduardo Yoshio, de Bragança Pereira, Carlos Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3770452/
https://www.ncbi.nlm.nih.gov/pubmed/23176636
http://dx.doi.org/10.1186/1471-2156-13-103
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author Izbicki, Rafael
Fossaluza, Victor
Hounie, Ana Gabriela
Nakano, Eduardo Yoshio
de Bragança Pereira, Carlos Alberto
author_facet Izbicki, Rafael
Fossaluza, Victor
Hounie, Ana Gabriela
Nakano, Eduardo Yoshio
de Bragança Pereira, Carlos Alberto
author_sort Izbicki, Rafael
collection PubMed
description BACKGROUND: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. RESULTS: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. CONCLUSIONS: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.
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spelling pubmed-37704522013-09-12 Testing allele homogeneity: the problem of nested hypotheses Izbicki, Rafael Fossaluza, Victor Hounie, Ana Gabriela Nakano, Eduardo Yoshio de Bragança Pereira, Carlos Alberto BMC Genet Methodology Article BACKGROUND: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. RESULTS: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. CONCLUSIONS: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations. BioMed Central 2012-11-23 /pmc/articles/PMC3770452/ /pubmed/23176636 http://dx.doi.org/10.1186/1471-2156-13-103 Text en Copyright © 2012 Izbicki 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 Methodology Article
Izbicki, Rafael
Fossaluza, Victor
Hounie, Ana Gabriela
Nakano, Eduardo Yoshio
de Bragança Pereira, Carlos Alberto
Testing allele homogeneity: the problem of nested hypotheses
title Testing allele homogeneity: the problem of nested hypotheses
title_full Testing allele homogeneity: the problem of nested hypotheses
title_fullStr Testing allele homogeneity: the problem of nested hypotheses
title_full_unstemmed Testing allele homogeneity: the problem of nested hypotheses
title_short Testing allele homogeneity: the problem of nested hypotheses
title_sort testing allele homogeneity: the problem of nested hypotheses
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3770452/
https://www.ncbi.nlm.nih.gov/pubmed/23176636
http://dx.doi.org/10.1186/1471-2156-13-103
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