# Example 1: Using SEAGLE with .txt Input Files

This tutorial demonstrates how to use the SEAGLE package when the user inputs $${\bf y}$$, $${\bf X}$$, $${\bf E}$$, and $${\bf G}$$ from .txt files. We’ll begin by loading the SEAGLE package.

library(SEAGLE)
#> Loading required package: CompQuadForm

If you have your own files ready to read in for $${\bf y}$$, $${\bf X}$$, $${\bf E}$$, and $${\bf G}$$, 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.

y_loc <- system.file("extdata", "y.txt", package = "SEAGLE")

X_loc <- system.file("extdata", "X.txt", package = "SEAGLE")

E_loc <- system.file("extdata", "E.txt", package = "SEAGLE")

G_loc <- system.file("extdata", "G.txt", package = "SEAGLE")
G <- as.matrix(read.csv(G_loc))

Now we can input $${\bf y}$$, $${\bf X}$$, $${\bf E}$$, and $${\bf G}$$ into the prep.SEAGLE function. The intercept = 1 parameter indicates that the first column of $${\bf X}$$ 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 $$\widetilde{\bf X} = \begin{pmatrix} {\bf 1}_{n} & {\bf X} & {\bf E} \end{pmatrix}$$, where $${\bf 1}_{n}$$ denotes the all ones vector of length $$n$$.

objSEAGLE <- prep.SEAGLE(y=as.matrix(y), X=X, intercept=1, E=E, G=G)

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 $$\tau$$ and $$\sigma$$ employed in the REML EM algorithm.

res <- SEAGLE(objSEAGLE, init.tau=0.5, init.sigma=0.5)
res$T #> [1] 246.1886 res$pv
#> [1] 0.8441451

The score-like test statistic $$T$$ for the G$$\times$$E effect and its corresponding p-value can be found in res$T and res$pv, respectively.