I have some idat files to analyze, since I haven’t found a complete script for doing it I have wrote one by myself:

library(limma)

# Files and experimental conditions
targets <- readTargets("targets.txt")  # I have two conditions "KO" and "WT"

# Reading data
idatfiles = dir(path="C:/Data", pattern = ".idat")
bgxfile = dir(path = "C:/Data", pattern = ".bgx")
data = read.idat(idatfiles, bgxfile)

# Normalization and background adjustment
data2 <- neqc(data)

# Build the design matrix for the linear modelling function. 
f <- factor(targets$Condition, levels = unique(targets$Condition))
design <- model.matrix(~0 + f)
colnames(design) <- levels(f)

# Apply the intensity values to lmFit. 
fit <- lmFit(data2, design)

# Create a contrast matrix. In this example, all combinations of contrasts can be set up as below. 
contrast.matrix <- makeContrasts("KO-WT",  levels=design)

# Apply this contrast matrix to the modeled data and compute statistics for the data.
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)

# Output the statistics for the dataset and write them to disk for further analysis.
output <- topTable(fit2, adjust="BH", coef="KO-WT", genelist=data2$genes, number=Inf)
write.table(output, file="Results.txt", sep="\t", quote=FALSE)

I have two questions, is it correct? Do you have any suggestion to improve it?

Thank you very much.