dear friends,

long time i am working on normalization my data with mas5...

i am really new in R, i have tried many tutorials, asking question in forums, etc to get the exact R codes for my purpose, but more i search more i am confused when copying and pasting the commands with the several errors...

for example i have GSE33964_RAW...i want to:

proccessing with MAS 5.0 and aligned into a matrix, romoving Genes not expressed (called absent) in ≥ 90 % of the microarray, condensing the matrix as a result, doing Pearson correlation coefficient (PCC)  to identify correlation relationships between my genes and other genes that passed filtering criteria using the ‘genefilter package’. each of my gene use as a query to identify the top 200 genes which shared the most similar expression profile based on PCC. This process is repeated, this time using all the genes identified in the previous step as query genes. In cases where both the my gene identified a co-expression partner and the co-expression partner identifiedwith my gene within the co-expression list of each query, the correlation is considered significant. The relationship between these nodes is summarized by drawing a line (edge) between the two genes (nodes) weighted by average rank and average PCC.

please someone patiently give me R codes using them i can at last normalize my data and achive a clue to normalization....

Here is some code for doing MAS 5 normalization in R. However, I would recommend that you try my SCAN.UPC package (http://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html) because it can handle any type of Affymetrix array (unlike MAS 5) and is easy to work with (in my opinion as the package's author).

library(affy)

library(methods)

inFilePattern = "*CEL.gz"

outFilePath = "GSE33964.matrix"

fileNames = list.files(pattern=glob2rx(inFilePattern))

rawData = ReadAffy(filenames=fileNames)

eset <- mas5(rawData)

write.exprs(eset, file=outFilePath, col.names=NA)

thank you Stephen

thank you very much Stephen, i did your proposed commands without error, now i have a file name GSE33964.matrix...

really sorry, may you tell me please the commands by which i can find correlated genes in this file with my intrested genes (genes involved in sterol biosynthesis pathway) doing Pearson correlation coefficient (PCC) using genefilter package?