Hi Gordon,

Dear Assa,
>
> It seems to me that the read.maimages() help page
>
>   help("read.maimages")
>
> answers your question.  The help page, for the version of limma that you
> are using, says
>
> "In the case of Agilent and GenePix, two possible foreground estimators
> are supported: source="genepix" uses the mean foreground estimates while
> source="genepix.median" uses median foreground estimates. Similarly for
> Agilent."
>


I have updated to the latest version of R (2.15.1) and limma (3.12.1).
I should have read the help page. But I read the User's manual (I think the
latest version - from June, 10th 2012).
The manual says differently (page 18):
the default values for agilent are not the same as for genepix.
by just stating 'source="agilent" ', limma takes both fore- and background
median signals.

So maybe the manual needs an update.


> So the help page tells you that read.maimages() reads the mean foreground
> by default, not the median foreground as you say in your email.  So if you
> override the default by reading in the median foreground, it is clear that
> you will get differing results.
>
> If you were to upgrade to the current version of R and the current version
> of limma, there much expanded documentation about reading Agilent files in
> the User's Guide (and the default for agilent has changed).
>
> Please note, I am happy to answer questions about current limma
> documentation.  However, if you follow a third party website that gives
> advice conflicting with the limma documentation, then you should send
> questions to the author of that website.
>

On this website, I just reacted to a comment supposedly made by you, or at
least was given by you. I did contact the guy who posted it, but he said he
can't help me. This is why I posted it here.

Again, thanks for clarifying the problem

Assa

>
> Best wishes
> Gordon
>
>  Date: Mon, 30 Jul 2012 17:16:12 +0200
>> From: Assa Yeroslaviz <frymor@gmail.com>
>> To: bioconductor <bioconductor@stat.math.ethz.**ch<bioconductor@stat.math.ethz.ch>
>> >
>> Subject: [BioC] read.maimages
>>
>> Hi BioC User,
>>
>> I am working for the first time on agilent CGH arrays (singel-channel).
>>
>> I would like to use the limma package for that>
>>
>> This is my script:
>>  >library(limma)
>>
>>  >targets <- readTargets("targets.txt")
>>  >x <- read.maimages(targets, path="rawData/",
>> source="agilent",green.only=**TRUE, names = targets$condition)
>>  >RG <- read.maimages(targets, path="rawData/", columns = list(G =
>> "gMedianSignal", Gb = "gBGMedianSignal", R = "gProcessedSignal",
>>   Rb = "gIsPosAndSignif"), annotation = c("Row", "Col","FeatureNum",
>> "ControlType","ProbeName"), names = targets$condition)
>>
>> I tried both examples as I've found an explanation mentioning both of
>> them (
>> here<http://matticklab.com/**index.php?title=Single_**
>> channel_analysis_of_Agilent_**microarray_data_with_Limma<http://matticklab.com/index.php?title=Single_channel_analysis_of_Agilent_microarray_data_with_Limma>
>> >).
>> My problem is that the results differs slightly from one another:
>>
>>  RG
>>>
>> An object of class "RGList"
>> $G
>>     controll 5_4_chr5 5_3_chr5 5_4_cp 5_3_growth 5_3_cp 5_3_growth
>> [1,]    363.0    374.0     1647 678.0      498.5 505.0        642
>> [2,]     34.0     24.0       27   34.5       31.0   34.0         31
>> [3,]     29.5     23.0       23   30.0       26.0   26.5         30
>> [4,]     31.0     23.0       28   28.0       27.0   31.0         29
>> [5,]     31.0     25.5       28   27.0       32.0   29.0         31
>> 45209 more rows ...
>>
>>  x
>>>
>> An object of class "EListRaw"
>> $E
>>      controll  5_4_chr5   5_3_chr5    5_4_cp 5_3_growth    5_3_cp
>> 5_3_growth
>> [1,] 361.30160 364.68250 1667.98200 683.31250  506.46670 502.66670
>> 649.01610
>> [2,]  34.84483  25.94737   29.00000  35.54839   32.28571  33.16949
>> 30.70492
>> [3,]  31.23438  25.46032   23.61905  31.90164   27.84127  28.95161
>> 30.82540
>> [4,]  31.65000  24.31818   27.72414  31.83607   28.85484  31.39683
>> 30.25000
>> [5,]  32.06349  25.93548   28.98413  28.25000   31.44615  28.04615
>> 30.78462
>> 45209 more rows ...
>>
>> Even though the differences are very small, I would still like to
>> understand them.
>> If I understood the manual correctly, limma takes by default the median
>> column for both fore- and background.
>> The background values are similar (x$Eb and RG$Eb).
>>
>> What columns does limma uses for the analysis?
>>
>>
>> I would appreciate the help
>>
>> thanks
>> Assa
>>
>>  sessionInfo()
>>>
>> R version 2.14.1 (2011-12-22)
>> Platform: x86_64-unknown-linux-gnu (64-bit)
>>
>> locale:
>> [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
>> [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
>> [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
>> [7] LC_PAPER=C                 LC_NAME=C
>> [9] LC_ADDRESS=C               LC_TELEPHONE=C
>> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>>
>> attached base packages:
>> [1] stats     graphics  grDevices utils     datasets  methods   base
>>
>> other attached packages:
>> [1] limma_3.10.3        BiocInstaller_1.2.1
>>
>> loaded via a namespace (and not attached):
>> [1] tools_2.14.1
>>
>
>
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