Bivariate Genome-Wide Association Study of Genetically Correlated Neuroimaging Phenotypes from DTI and MRI through a Seemingly Unrelated Regression Model.
Neda JahanshadPriya BhattDerrek P. HibarJulio VillalonTalia M. NirArthur W. TogaClifford R. Jack Jr.Matt A. BernsteinMichael W. WeinerKatie McMahonGreig I. de ZubicarayNicholas G. MartinMargaret J. WrightPaul M. ThompsonPublished in: MBIA (2013)
Keyphrases
- regression model
- genome wide association studies
- seemingly unrelated
- clinical studies
- functional mri
- white matter
- human brain
- brain images
- diffusion tensor imaging
- genome wide
- brain tissue
- magnetic resonance imaging
- magnetic resonance images
- complex diseases
- mr images
- biological data
- functional magnetic resonance imaging
- medical images
- mri data
- diffusion tensor
- regression methods
- human genome
- model selection
- complex networks
- generalized linear models
- highly correlated
- regression analysis
- explanatory variables
- magnetic resonance
- risk factors
- high throughput
- data analysis
- single nucleotide polymorphisms
- interval valued data
- tensor field
- medical imaging
- multivariate regression
- average precision
- dna sequences
- gene expression
- data integration
- feature selection