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

Mon May 28 11:51:29 CEST 2012

Dear Parisa,

The problem is not to do with the file format.  The problem is almost 
certainly that you are trying to read data files from different GEO series 
that contain different numbers of rows (probes), and read.maimages() does 
not allow you to do that.

As the help page for read.maimages says, "All image analysis files being 
read are assumed to contain data for the same genelist in the same order."

Does it make sense to combine the different GEO series?  Did they all use 
exactly the same Agilent array?  If it does make sense, but the data files 
contain data for different sets of probe, then it is up to you read the 
series into R separately, then to make decisions about which probes can be 
matched up across series and which cannot.

Best wishes
Gordon

-------------- original message -----------------
[BioC] File format for single channel analysis of Agilent microarray data 
with Limma?
Parisa Razaz Parisa.Razaz at icr.ac.uk
Sun May 27 20:09:13 CEST 2012

Hi Guido,

Thank you for getting back to me. I am also using data downloaded from GEO 
and have now incorporated your suggestion of "agilent.median" when using 
the read.maimages function. However the problem now appears to be with 
loading files from different series (when using the read.maimages 
function).  Particular combinations of series work and others don't, with 
those that don't giving the same error message as before. I thought that 
this may be a size limit issue, but the combined number of samples for 
some of the series that don't work together is smaller at times than those 
that do. Do you have any idea why this might be and how I would get around 
it?

Thanks,

Parisa

________________________________________
From: Hooiveld, Guido [Guido.Hooiveld at wur.nl]
Sent: 23 May 2012 16:52
To: bioconductor at r-project.org; Parisa Razaz
Subject: RE: [BioC] File format for single channel analysis of Agilent 
microarray data with Limma?

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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