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.
Thank you, I' ll check it
Can you please update the link? Thanks.
I tried but gave up since the debugging takes longer than creating my own script. Some errors below: