scholarly journals Sequence Kernel Association Test for Quantitative Traits in Family Samples

2012 ◽  
Vol 37 (2) ◽  
pp. 196-204 ◽  
Author(s):  
Han Chen ◽  
James B. Meigs ◽  
Josée Dupuis
Keyword(s):  
Quantitative Traits ◽  
Association Test ◽  
Sequence Kernel Association Test

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT)

2015 ◽  
Vol 8 (4) ◽  
pp. 495-505 ◽  
Author(s):  
Eugene Urrutia ◽  
Seunggeun Lee ◽  
Arnab Maity ◽  
Ni Zhao ◽  
Judong Shen ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Test ◽  
Sequence Kernel Association Test

A Family-Based Association Test for Repeatedly Measured Quantitative Traits Adjusting for Unknown Environmental and/or Polygenic Effects

2004 ◽  
Vol 3 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Christoph Lange ◽  
Kristel van Steen ◽  
Toby Andrew ◽  
Helen Lyon ◽  
Dawn L DeMeo ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Software Package ◽  
Quantitative Traits ◽  
Univariate Analysis ◽  
Principal Component ◽  
Genetic Effects ◽  
Association Test ◽  
Practical Relevance ◽  
Simulation Studies ◽  
Family Based

We propose a family-based association test, FBAT-PC, for studies with quantitative traits that are measured repeatedly. The traits may be influenced by partially or completely unknown factors that may vary for each measurement. Using generalized principal component analysis, FBAT-PC amplifies the genetic effects of each measurement by constructing an overall phenotype with maximal heritability. Analytically, and in the simulation studies, we compare FBAT-PC with standard methodology and assess both the heritability of the overall phenotype and the power of FBAT-PC. Compared to univariate analysis, FBAT-PC achieves power gains of up to 200%. Applications of FBAT-PC to an osteoporosis study and to an asthma study show the practical relevance of FBAT-PC. FBAT-PC has been implemented in the software package PBAT and is freely available at http://www.biostat.harvard.edu/~clange/default.htm.

scholarly journals A Sequence Kernel Association Test for Dichotomous Traits in Family Samples under a Generalized Linear Mixed Model

2015 ◽  
Vol 79 (2) ◽  
pp. 60-68 ◽  
Author(s):  
Qi Yan ◽  
Hemant K. Tiwari ◽  
Nengjun Yi ◽  
Guimin Gao ◽  
Kui Zhang ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Association Test ◽  
Sequence Kernel Association Test

scholarly journals Sequence Kernel Association Test for Survival Traits

2014 ◽  
Vol 38 (3) ◽  
pp. 191-197 ◽  
Author(s):  
Han Chen ◽  
Thomas Lumley ◽  
Jennifer Brody ◽  
Nancy L. Heard-Costa ◽  
Caroline S. Fox ◽  
...  
Keyword(s):  
Association Test ◽  
Sequence Kernel Association Test

scholarly journals Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test

2011 ◽  
Vol 89 (1) ◽  
pp. 82-93 ◽  
Author(s):  
Michael C. Wu ◽  
Seunggeun Lee ◽  
Tianxi Cai ◽  
Yun Li ◽  
Michael Boehnke ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Test ◽  
Sequence Kernel Association Test ◽  
Sequencing Data ◽  
Rare Variant Association ◽  
Association Testing

scholarly journals Sequence Kernel Association Test of Multiple Continuous Phenotypes

2016 ◽  
Vol 40 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Baolin Wu ◽  
James S. Pankow
Keyword(s):  
Association Test ◽  
Sequence Kernel Association Test
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