ArticleBMC proceedings2016
Joint analysis of multiple blood pressure phenotypes in GAW19 data by using a multivariate rare-variant association test.
Article in BMC proceedings, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A fast and powerful aggregated Cauchy association test for joint analysis of multiple phenotypes.Genes & genomics · 2021Article
- A permutation method for detecting trend correlations in rare variant association studies.Genetics research · 2019Article
- Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes.Genetic epidemiology · 2019Article
- Association analysis of rare and common variants with multiple traits based on variable reduction method.Genetics research · 2018Article
- Joint analysis of multiple phenotypes: summary of results and discussions from the Genetic Analysis Workshop 19.BMC genetics · 2016Article
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Authors and funding
5 authors.
Funding
Abstract
introductionLarge-scale sequencing studies often measure many related phenotypes in addition to the genetic variants. Joint analysis of multiple phenotypes in genetic association studies may increase power to detect disease-associated loci.
methodsWe apply a recently developed multivariate rare-variant association test to the Genetic Analysis Workshop 19 data in order to test associations between genetic variants and multiple blood pressure phenotypes simultaneously. We also compare this multivariate test with a widely used univariate test that analyzes phenotypes separately.
resultsThe multivariate test identified 2 genetic variants that have been previously reported as associated with hypertension or coronary artery disease. In addition, our region-based analyses also show that the multivariate test tends to give smaller
conclusionsHence, the multivariate test has potential to improve test power, especially when multiple phenotypes are correlated.
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