ArticlePloS one2009
Family-based bivariate association tests for quantitative traits.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Identification of pleiotropic loci underlying hip bone mineral density and trunk lean mass.Journal of human genetics · 2021Pooled it
- Four pleiotropic loci associated with fat mass and lean mass.International journal of obesity (2005) · 2020Pooled it
- Two novel pleiotropic loci associated with osteoporosis and abdominal obesity.Human genetics · 2020Pooled it
- 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
- Bivariate genetic association of KIAA1797 with heart rate in American Indians: the Strong Heart Family Study.Human molecular genetics · 2010Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The availability of a large number of dense SNPs, high-throughput genotyping and computation methods promotes the application of family-based association tests. While most of the current family-based analyses focus only on individual traits, joint analyses of correlated traits can extract more information and potentially improve the statistical power. However, current TDT-based methods are low-powered. Here, we develop a method for tests of association for bivariate quantitative traits in families. In particular, we correct for population stratification by the use of an integration of principal component analysis and TDT. A score test statistic in the variance-components model is proposed. Extensive simulation studies indicate that the proposed method not only outperforms approaches limited to individual traits when pleiotropic effect is present, but also surpasses the power of two popular bivariate association tests termed FBAT-GEE and FBAT-PC, respectively, while correcting for population stratification. When applied to the GAW16 datasets, the proposed method successfully identifies at the genome-wide level the two SNPs that present pleiotropic effects to HDL and TG traits.
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Registered trials
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