This tutorial demonstrates how to use the SEAGLE
package when the user inputs y, X, E, and G from .txt files. We’ll begin by loading the SEAGLE
package.
library(SEAGLE)
#> Loading required package: Matrix
#> Loading required package: CompQuadForm
If you have your own files ready to read in for y, X, E, and G, you can read them into R using the read.csv()
command.
As an example, we’ve included y.txt
, X.txt
, E.txt
, and G.txt
files in the extdata
folder of this package. The following code loads those files into R so we can use them in this tutorial.
<- system.file("extdata", "y.txt", package = "SEAGLE")
y_loc <- as.numeric(unlist(read.csv(y_loc)))
y
<- system.file("extdata", "X.txt", package = "SEAGLE")
X_loc <- as.matrix(read.csv(X_loc))
X
<- system.file("extdata", "E.txt", package = "SEAGLE")
E_loc <- as.numeric(unlist(read.csv(E_loc)))
E
<- system.file("extdata", "G.txt", package = "SEAGLE")
G_loc <- as.matrix(read.csv(G_loc)) G
Now we can input y, X, E, and G into the prep.SEAGLE
function. The intercept = 1
parameter indicates that the first column of X is the all ones vector for the intercept.
This preparation procedure formats the input data for the SEAGLE
function by checking the dimensions of the input data. It also pre-computes a QR decomposition for ˜X=(1nXE), where 1n denotes the all ones vector of length n.
<- prep.SEAGLE(y=as.matrix(y), X=X, intercept=1, E=E, G=G) objSEAGLE
Finally, we’ll input the prepared data into the SEAGLE
function to compute the score-like test statistic T and its corresponding p-value. The init.tau
and init.sigma
parameters are the initial values for τ and σ employed in the REML EM algorithm.
<- SEAGLE(objSEAGLE, init.tau=0.5, init.sigma=0.5)
res $T
res#> [1] 246.1886
$pv
res#> [1] 0.8441451
The score-like test statistic T for the G×E effect and its corresponding p-value can be found in res$T
and res$pv
, respectively.