I am analyzing microarray data. I am using a new normalization approach which outputs into a gene matrix text file.
Normally I take raw CEL files and use "ReadAffy" function, plot a raw boxplot, normalize with RMA, then plot a normalized boxplot following I write it to a gene matrix, something like this:
raw <- ReadAffy(filenames = sampleNames(pd), phenoData = pd, sampleNames = pd$SampleName) boxplot(raw) normalized <- gcrma(raw) boxplot(normalized) matrix <- exprs(normalized) write.table(matrix, file = "geneMatrix.txt") PsetNormalized <- fitPLM(raw, background.method=”GCRMA”) # Plots the RLE graph Mbox(PsetNormalized) # Plots the NUSE graph boxplot(PsetNormalized)
Currently, my normalization approach takes CEL files and outputs then directly into a log2 value gene matrix. Is there a function I can use to take a gene matrix with log2 values and create such box plots and later RLE and NUSE plots?
Any suggestions are grateful.