[BioC] File format for single channel analysis of Agilent microarray data with Limma?

[Hooiveld, Guido]

Hi Parisa,

I also once struggled with reading in some Agilent singe channel arrays (that I downloaded from GEO; GSE27784), but for me these line of codes worked (in particularly note that the 2nd line is different than the one that is given on the website you linked to; specifically the statement source="agilent.median"):

HTH,
Guido

> 
> targets <- readTargets("targets_GSE27784.txt", row.names="Name")
> e.raw <- read.maimages(targets$FileName, source="agilent.median", green.only=TRUE)
Read GSM686624_251486829200_S01_GE1_105_Jan09_1_1.txt 
Read GSM686625_251486829201_S01_GE1_105_Jan09_1_2.txt 
Read GSM686626_251486829328_S01_GE1_105_Jan09_1_3.txt 
Read GSM686627_251486829200_S01_GE1_105_Jan09_1_2.txt 
Read GSM686628_251486829200_S01_GE1_105_Jan09_1_4.txt 
Read GSM686629_251486829201_S01_GE1_105_Jan09_1_4.txt 
Read GSM686630_251486829328_S01_GE1_105_Jan09_1_4.txt 
Read GSM686631_251486829328_S01_GE1_105_Jan09_1_1.txt 
Read GSM686632_251486829328_S01_GE1_105_Jan09_1_2.txt 
Read GSM686633_251486829200_S01_GE1_105_Jan09_1_3.txt 
Read GSM686634_251486829201_S01_GE1_105_Jan09_1_3.txt 
Read GSM686635_251486829201_S01_GE1_105_Jan09_1_1.txt 
> 
> #Background correction using normexp + offset
> e.raw2 <- backgroundCorrect(e.raw, method="normexp", offset=50)
Array 1 corrected
Array 2 corrected
Array 3 corrected
Array 4 corrected
Array 5 corrected
Array 6 corrected
Array 7 corrected
Array 8 corrected
Array 9 corrected
Array 10 corrected
Array 11 corrected
Array 12 corrected
>
> # Perform quantile normalization
> expr.data <- normalizeBetweenArrays(e.raw2, method="quantile") 
>
> #Use the avereps function to average replicate spots.
> E.avg <- avereps(expr.data, ID=expr.data$genes$ProbeName)
>
>
> # Alternatively, perform background correction using the negative control probes + quantile normalization
> table(e.raw$genes$ControlType)

   -1     0     1 
  153 43379  1486 
> bg.corr <- neqc(e.raw, status=e.raw$genes$ControlType, negctrl=-1, regular=0)
> 
> E.avg <- avereps(bg.corr, ID=bg.corr$genes$ProbeName)
>


--------------------------------------------------------- 
Guido Hooiveld, PhD 
Nutrition, Metabolism & Genomics Group 
Division of Human Nutrition 
Wageningen University 
Biotechnion, Bomenweg 2 
NL-6703 HD Wageningen 
the Netherlands 
tel: (+)31 317 485788 
fax: (+)31 317 483342 
email:      guido.hooiveld at wur.nl
internet:   http://nutrigene.4t.com 
http://scholar.google.com/citations?user=qFHaMnoAAAAJ
http://www.researcherid.com/rid/F-4912-2010

-----Original Message-----
From: bioconductor-bounces at r-project.org [mailto:bioconductor-bounces at r-project.org] On Behalf Of Parisa [guest]
Sent: Wednesday, May 23, 2012 15:51
To: bioconductor at r-project.org; parisa.razaz at icr.ac.uk
Subject: [BioC] File format for single channel analysis of Agilent microarray data with Limma?


Hi,

I am following the protocol outlined here for analysis of single channel Agilent microarray data: 

http://matticklab.com/index.php?title=Single_channel_analysis_of_Agilent_microarray_data_with_Limma

I keep getting the following error message when using Limma's read.maimages function to load my data into an RGList object: 

Error in RG[[a]][, i] <- obj[, columns[[a]]] :
  number of items to replace is not a multiple of replacement length 

I think this may be due to my Agilent raw data txt files being in the wrong format. I am having difficulty finding an example Agilent feature extraction raw data txt file online to compare it to. A link to a screen shot of one of the files I am using is below. I would appreciate if someone could let me know if it is in the correct format, and if not then what format it should be in to prevent the above error message from coming up. 

Thank you,

Parisa 

http://www4.picturepush.com/photo/a/8322602/img/8322602.png

 -- output of sessionInfo(): 

> sessionInfo()R version 2.13.1 (2011-07-08)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/C/C/en_GB.UTF-8/en_GB.UTF-8

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

other attached packages:
[1] limma_3.8.3


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