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Extension of the generalized disequilibrium test to polytomous phenotypes and two-locus models.

ABSTRACT: WE EXTEND THE USUAL LOGISTIC MODEL BETWEEN A DICHOTOMOUS PHENOTYPE AND AN ALLELE COUNT IN TWO WAYS: a polytomous phenotype with K > 2 levels, and modeling of allele counts at two unlinked marker loci. Inference is based on within-family information to guard against potential bias due to population genetic structure. Score tests of the model coefficients taking into account the correlation between relatives in entire pedigrees are derived as an extension of the Generalized Disequilibrium Test (GDT). Simulations confirm that the tests have the expected statistical properties, and that their power exceeds that of the GDT under a favorable scenario. The score tests are illustrated with candidate genetic markers, a major psychosis phenotype and a cognitive endophenotype in large kindreds from Eastern Quebec.

SUBMITTER: Bureau A

PROVIDER: S-EPMC4126369 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Extension of the generalized disequilibrium test to polytomous phenotypes and two-locus models.

Bureau Alexandre A Croteau Jordie J Chagnon Yvon C YC Roy Marc-André MA Maziade Michel M

Frontiers in genetics 20140808

WE EXTEND THE USUAL LOGISTIC MODEL BETWEEN A DICHOTOMOUS PHENOTYPE AND AN ALLELE COUNT IN TWO WAYS: a polytomous phenotype with K > 2 levels, and modeling of allele counts at two unlinked marker loci. Inference is based on within-family information to guard against potential bias due to population genetic structure. Score tests of the model coefficients taking into account the correlation between relatives in entire pedigrees are derived as an extension of the Generalized Disequilibrium Test (GD ...[more]

PMID: 25152751

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Project description:BackgroundFor dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist.ResultsIn this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease.ConclusionsUnder complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice.

Dataset Information

Extension of the generalized disequilibrium test to polytomous phenotypes and two-locus models.

Publications

Extension of the generalized disequilibrium test to polytomous phenotypes and two-locus models.

Similar Datasets

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