Question: R: Gene Matrix (.Txt File) To Boxplot And Rle, Nuse Plots
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gravatar for michaelsbreen1
8.1 years ago by
University of Southampton
michaelsbreen180 wrote:

Hi all,

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.

Thank you,

Michael

R microarray • 4.4k views
ADD COMMENTlink modified 8.1 years ago by Sean Davis26k • written 8.1 years ago by michaelsbreen180
1
gravatar for Sean Davis
8.1 years ago by
Sean Davis26k
National Institutes of Health, Bethesda, MD
Sean Davis26k wrote:

If you have a matrix of values, you can plot a boxplot easily:

# an example:
m = matrix(rnorm(100000),nc=10)
boxplot(m)

If you have probeset-level data rather than gene-level data, I think you should be able to reproduce an RLE plot. As for NUSE, that will not be possible without probe-level data. That said, is there a reason not to use the .CEL files to produce the NUSE and RLE plots? These plots should still useful for QC of the arrays regardless of the normalization method.

ADD COMMENTlink written 8.1 years ago by Sean Davis26k
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