| GxE {GRSxE} | R Documentation |
Testing individual gene-environment interactions
Description
Function for testing univariate GxE interactions, e.g., using single SNPs or a GRS.
Usage
GxE(G, y, E, C = NULL)
Arguments
G |
Numeric vector of a genetic variable such as a GRS (genetic risk score) or a SNP coded as 0-1-2. |
y |
Numeric vector of the outcome/phenotype. Binary outcomes such as a disease status should be coded as 0-1 (control-case). |
E |
Numeric vector of the environmental exposure. |
C |
Optional data frame containing potentially confounding variables to be adjusted for. |
Details
This function uses a GLM (generalized linear model) for modelling the
marginal genetic effect, marginal environmental effect, the GxE interaction
effect, and potential confounding effects.
The fitted GLM is returned, which can be, e.g., inspected via
summary(...) to retrieve the Wald test p-values for the individual
terms. The p-value corresponding to the G:E term is the p-value
for testing the presence of a GxE interaction.
Value
An object of class glm is returned, in which G:E
describes the GxE term.
References
Lau, M., Kress, S., Schikowski, T. & Schwender, H. (2023). Efficient gene–environment interaction testing through bootstrap aggregating. Scientific Reports 13:937. doi: 10.1038/s41598-023-28172-4