ArticleAmerican journal of human genetics2006
A flexible Bayesian framework for modeling haplotype association with disease, allowing for dominance effects of the underlying causative variants.
Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- A multivariate Bernoulli model to predict DNaseI hypersensitivity status from haplotype data.Bioinformatics (Oxford, England) · 2015Article
- Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping.PLoS genetics · 2015Article
- Imputation without doing imputation: a new method for the detection of non-genotyped causal variants.Genetic epidemiology · 2014Article
- Haplotype estimation using sequencing reads.American journal of human genetics · 2013Article
- A fast expectation-maximum algorithm for fine-scale QTL mapping.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
- Article
- Comparison of multimarker logistic regression models, with application to a genomewide scan of schizophrenia.BMC genetics · 2010Article
- High-density SNP association study and copy number variation analysis of the AUTS1 and AUTS5 loci implicate the IMMP2L-DOCK4 gene region in autism susceptibility.Molecular psychiatry · 2010Article
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- The diverse applications of cladistic analysis of molecular evolution, with special reference to nested clade analysis.International journal of molecular sciences · 2010Review
- An update on the genetics of atopic dermatitis: scratching the surface in 2009.The Journal of allergy and clinical immunology · 2010Review
- Association of FTO variants with BMI and fat mass in the self-contained population of Sorbs in Germany.European journal of human genetics : EJHG · 2010Article
- The role of CACNA1S in predisposition to malignant hyperthermia.BMC medical genetics · 2009Article
- SHARE: an adaptive algorithm to select the most informative set of SNPs for candidate genetic association.Biostatistics (Oxford, England) · 2009Article
- Association mapping by generalized linear regression with density-based haplotype clustering.Genetic epidemiology · 2009Article
- VACTERL/caudal regression/Currarino syndrome-like malformations in mice with mutation in the proprotein convertase Pcsk5.Genes & development · 2008Article
- Imputation-based analysis of association studies: candidate regions and quantitative traits.PLoS genetics · 2007Article
- Genetic association mapping via evolution-based clustering of haplotypes.PLoS genetics · 2007Article
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Abstract
Multilocus analysis of single-nucleotide-polymorphism (SNP) haplotypes may provide evidence of association with disease, even when the individual loci themselves do not. Haplotype-based methods are expected to outperform single-SNP analyses because (i) common genetic variation can be structured into haplotypes within blocks of strong linkage disequilibrium and (ii) the functional properties of a protein are determined by the linear sequence of amino acids corresponding to DNA variation on a haplotype. Here, I propose a flexible Bayesian framework for modeling haplotype association with disease in population-based studies of candidate genes or small candidate regions. I employ a Bayesian partition model to describe the correlation between marker-SNP haplotypes and causal variants at the underlying functional polymorphism(s). Under this model, haplotypes are clustered according to their similarity, in terms of marker-SNP allele matches, which is used as a proxy for recent shared ancestry. Haplotypes within a cluster are then assigned the same probability of carrying a causal variant at the functional polymorphism(s). In this way, I can account for the dominance effect of causal variants, here corresponding to any deviation from a multiplicative contribution to disease risk. The results of a detailed simulation study demonstrate that there is minimal cost associated with modeling these dominance effects, with substantial gains in power over haplotype-based methods that do not incorporate clustering and that assume a multiplicative model of disease risks.
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