ArticleAnnals of human genetics2009
Multivariate association test using haplotype trend regression.
Article in Annals of human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Bivariate quantitative Bayesian LASSO for detecting association of rare haplotypes with two correlated continuous phenotypes.Frontiers in genetics · 2023Article
- Genome-Wide Association Analyses Track Genomic Regions for Resistance toFrontiers in plant science · 2022Article
- Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes.Genetic epidemiology · 2019Article
- Bivariate genome-wide association analyses identified genetic pleiotropic effects for bone mineral density and alcohol drinking in Caucasians.Journal of bone and mineral metabolism · 2017Article
- Suggestion of GLYAT gene underlying variation of bone size and body lean mass as revealed by a bivariate genome-wide association study.Human genetics · 2013Article
- Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions.BMC systems biology · 2013Article
- A post-GWAS replication study confirming the PTK2 gene associated with milk production traits in Chinese Holstein.PloS one · 2013Article
- Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.European journal of human genetics : EJHG · 2011Article
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Authors and funding
4 authors.
Funding
Abstract
Genetic association analyses with haplotypes may be more powerful than analyses with single markers, under certain conditions. Furthermore, simultaneously considering multiple correlated traits may make use of additional information that would not be considered when analyzing individual traits. In this study, we propose a haplotype based test of association for multivariate quantitative traits in unrelated samples. Specifically, we extend a population based haplotype trend regression (HTR) approach to multivariate scenarios. We mainly focused on bivariate HTR, and the simulation results showed that the proposed method had correct pre-specified type-I error rates. The power of the proposed method was largely influenced by the size and source of correlation between variables, being greatest when correlation of a specific gene was opposite in sign to the residual correlation.
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Registered trials
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