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R_CHP Production

Convert an Affy CEL file into Affymetrix like Mas5.0 signal and detection calls using R/Bioconductor This is the same method used to produce the data which is loaded into SBEAMS. Please note that these files can also be downloaded from SBEAMS.

Users
pmoss

What was done

Obtain CEL files:

(http://db/sbeams/cgi/Microarray/main.cgi)

Choose the 'Project Home' button on the left side of the screen

Choose the 'Data Download' tab along the top of the page

Make sure you have the appropriate project selected in the project chooser drop-down on the top of the page--you should see your Affy chips listed on the page

Check the box under CEL for each chip you'd like to analyze

Click the 'GET_AFFY_ARRAY_FILES' button underneath the chip listing, and save these somewhere on your computer.

Unzip the downloaded file to get the actual CEL files.

Open Link

Get Project Home Help

Use R/Bioconductor:

Use the following steps to set up and run R/Bioconductor:

R can be downloaded from

(http://www.r-project.org)

2) Bioconductor packages can be installed by running within R:


source("http://www.bioconductor.org/getBioC.R")
getBioC()

3) Use the following code to load in a CEL file and export a datafile plus a image of the array. Please note that you will have to supply path names for the variable $cel_file, $out_R_CHP_file, $out_chip_image.


switch(.Platform$OS.type, unix = .libPaths("/net/arrays/Affymetrix/bioconductor/library/"),"windows")
	.libPaths("$R_library")
library(affy)
cel.file.name    <- c("$cel_file")
output.file.name <- c("$out_R_CHP_file")
data <- ReadAffy(filenames =  cel.file.name)

eset <- mas5(data,sc=250)
PACalls <- mas5calls(data,alpha1=0.05,alpha2=0.065)

Matrix <- exprs(eset)
output <- cbind(row.names(Matrix),Matrix,exprs(PACalls),se.exprs(PACalls))
headings <- c("Probesets","MAS5_Signal","MAS5_Detection_calls", "MAS5_Detection_p-value")
write.table(output,file=output.file.name,sep="\\t",col.names = headings,row.names=FALSE)



jpeg("$out_chip_image", width=1000, height=1000)
image( data[,1] )
dev.off()
END