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}}