Equivalence of kernel machine regression and kernel distance covariance for multidimensional phenotype association studies

Associating genetic markers with a multidimensional phenotype is an important yet challenging problem. In this work, we establish the equivalence between two popular methods: kernel-machine regression (KMR), and kernel distance covariance (KDC). KMR is a semiparametric regression framework that mode...

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Veröffentlicht in:	Biometrics 2015-09, Vol.71 (3), p.812-820
Hauptverfasser:	Hua, Wen-Yu, Ghosh, Debashis
Format:	Artikel
Sprache:	eng
Schlagworte:	Alzheimer Disease - diagnosis Alzheimer Disease - epidemiology Alzheimer Disease - genetics Analysis of Variance BIOMETRIC PRACTICE Computer Simulation Confounding Data Interpretation, Statistical Distance covariance Genetic Association Studies - methods Genetic markers Genetic Markers - genetics Genetic Predisposition to Disease - epidemiology Genetic Predisposition to Disease - genetics Genotype & phenotype Hilbert-Schmidt independence criterion Models, Statistical Neuroimaging genomics Permutation test Polymorphism, Single Nucleotide - genetics Prevalence Regression Analysis Reproducibility of Results Risk Factors Sensitivity and Specificity
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