[BioC] Producing MA plots for single channel agilent data

[Lesley Hoyles [guest]]

Hi

I'm a newbie to Bioconductor and am trying to implement QC into a pipeline I am building for analysing Agilent data.

I have followed the very good code given in 'Single channel analysis of Agilent microarray data with Limma' and implemented it in Python with the R interface (RPy2) and have been able to generate an output file of differential gene expression data. However, I want to be able to look at MA plots for the normalized data prior to producing the differential data so that I can assess whether normalization has done its job. I also want to be able to save each of the normalized arrays to files for other analyses. I have looked at the outputs of the various R steps but have been unable to identify where the relevant M and A data are. I have pasted the relevant part of my code below.

Any help/advice with regard to my two queries would be greatly appreciated.

Thanks
Lesley

-----------------------------------------
robjects.r.library("limma")

#Normalization
robjects.r('targets <- readTargets("target.txt")') #Read in tab-delimited 'target.txt' file (contains names of raw data file and corresponding sample information)
robjects.r('x <- read.maimages(targets, path="microarray_raw_data/", source="agilent",green.only=TRUE)') #Load data into a list object
robjects.r('y <- backgroundCorrect(x, method="normexp", offset=16)') #Subtract the background
robjects.r('y <- normalizeBetweenArrays(y, method="quantile")') #Normalize the green channel between the arrays; quantile normalization is part of RMA and normalizes a batch of arrays to make further comparisons meaningful
robjects.r('y.ave <- avereps(y, ID=y$genes$ProbeName)') #Use the avereps function to average replicate spots

 -- output of sessionInfo(): 

R version 2.15.0 (2012-03-30)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.utf8       LC_NUMERIC=C             
 [3] LC_TIME=en_US.utf8        LC_COLLATE=en_US.utf8    
 [5] LC_MONETARY=en_US.utf8    LC_MESSAGES=en_US.utf8   
 [7] LC_PAPER=C                LC_NAME=C                
 [9] LC_ADDRESS=C              LC_TELEPHONE=C           
[11] LC_MEASUREMENT=en_US.utf8 LC_IDENTIFICATION=C      

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base 

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