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: mat="" ticklab.com="" index.php?title="Single_channel_analysis_of_Agilent_microar" ray_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
>>
>
>
> ______________________________**______________________________**____
______
> The information in this email is confidential and
inte...{{dropped:10}}
Dear Assa,
No, the User's Guide is correct. As I said in my last email, the default for agilent has changed between the older version that you were using and the current version. The documentation with each version of limma correctly describes the behaviour of that version of the software.
Best wishes
Gordon