Package: LEGIT
Title: Latent Environmental & Genetic InTeraction (LEGIT) Model
Version: 1.0.2
Date: 2017-03-23
Author: Alexia Jolicoeur-Martineau <alexia.jolicoeur-martineau@mail.mcgill.ca>
Maintainer: Alexia Jolicoeur-Martineau <alexia.jolicoeur-martineau@mail.mcgill.ca>
Description: Constructs genotype x environment interaction (GxE) models where
G is a weighted sum of genetic variants (genetic score) and E is a weighted
sum of environments (environmental score) using the alternating optimization algorithm
by Jolicoeur-Martineau et al. (2017) <arXiv:1703.08111>. Alternating optimization is
an iterative process where the genetic score weights, the environmental score weights,
and the main model parameters are estimated in turn assuming the other parameters to
be constant. This approach has greatly enhanced predictive power over traditional GxE
models which include only a single genetic variant and a single environmental
exposure. Gene x gene interactions (GxG) and environment x environment interactions
(ExE) can be incorporated into the genetic and environmental scores. Any standard
model formula can be used, it doesn't have to be a two-way interaction model.
Although this approach was made for GxE modelling, the genetic score doesn't need to
contain genetic variables and the environmental score doesn't need to contain
environmental variables, therefore this approach is highly flexible.
License: GPL-3
Imports: pROC
Depends: formula.tools, stats
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-04-02 22:06:37 UTC; Alexia
Repository: CRAN
Date/Publication: 2017-04-02 23:34:54 UTC

Package: LEGIT
Title: Latent Environmental & Genetic InTeraction (LEGIT) Model
Version: 1.0.3
Date: 2017-04-09
Author: Alexia Jolicoeur-Martineau <alexia.jolicoeur-martineau@mail.mcgill.ca>
Maintainer: Alexia Jolicoeur-Martineau <alexia.jolicoeur-martineau@mail.mcgill.ca>
Description: Constructs genotype x environment interaction (GxE) models where
G is a weighted sum of genetic variants (genetic score) and E is a weighted
sum of environments (environmental score) using the alternating optimization algorithm
by Jolicoeur-Martineau et al. (2017) <arXiv:1703.08111>. Alternating optimization is
an iterative process where the genetic score weights, the environmental score weights,
and the main model parameters are estimated in turn assuming the other parameters to
be constant. This approach has greatly enhanced predictive power over traditional GxE
models which include only a single genetic variant and a single environmental
exposure. Gene x gene interactions (GxG) and environment x environment interactions
(ExE) can be incorporated into the genetic and environmental scores. Any standard
model formula can be used, it doesn't have to be a two-way interaction model.
Although this approach was made for GxE modelling, the genetic score doesn't need to
contain genetic variables and the environmental score doesn't need to contain
environmental variables, therefore this approach is highly flexible.
License: GPL-3
Imports: pROC
Depends: formula.tools, stats
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-04-09 21:42:45 UTC; Alexia
Repository: CRAN
Date/Publication: 2017-04-09 22:14:46 UTC