I am an absolut beginner in R and limma. I would like to analyze 2 colour microarray data (GSE37326): normalization, quality control, estimate diff. genes I am only interested in finding diff. genes for one substance (slides: GSM915419_NP_1, GSM915420_NP_2 and GSM915421_NP_3). targets.txt SampleNumber FileName Cy3 Cy5 1 GSM915419_NP_1.txt DMSO NP 2 GSM915420_NP_2.txt DMSO NP 3 GSM915421_NP_3.txt DMSO NP Is this correct for my files? > targets <- readTargets("targets_test_.txt") > RG <- read.maimages(targets, columns=list(R="F635 Median",G="F532 Median",Rb="B635",Gb="B532")) > MA <- normalizeWithinArrays(RG, method="loess") > fit <- lmFit(MA) > fit <- eBayes(fit) > output <- topTable(fit2, adjust="BH", coef="NP", number=100000) > write.table(output, file="NP_vs_DMSO_15072014.txt", sep="t", quote=FALSE) I am really not sure if the output table is correct (especially my use of read.maimages?). How to perform a ???Quality assessment??? before and after normalization? How to get gene annotation? Any feedback is very welcome. Thanks and best regards, Jeannette -- output of sessionInfo(): R version 3.0.2 (2013-09-25) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C [5] LC_TIME=German_Germany.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] limma_3.18.13 affy_1.40.0 Biobase_2.22.0 BiocGenerics_0.8.0 loaded via a namespace (and not attached): [1] affyio_1.30.0 BiocInstaller_1.12.1 preprocessCore_1.24.0 [4] tools_3.0.2 zlibbioc_1.8.0 R version 3.0.2 (2013-09-25) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C [5] LC_TIME=German_Germany.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] limma_3.18.13 affy_1.40.0 Biobase_2.22.0 BiocGenerics_0.8.0 loaded via a namespace (and not attached): [1] affyio_1.30.0 BiocInstaller_1.12.1 preprocessCore_1.24.0 [4] tools_3.0.2 zlibbioc_1.8.0 -- Sent via the guest posting facility at bioconductor.org.

Dear Jeannette, GSE37326 is using standard Agilent arrays, so you could set the source argument to read.maimages to "agilent" and it should find the right columns from your text files. Otherwise see the annotation argument in ?read.maimages in order to get gene annotation. You should certainly not use fit2 in your call to topTable() if you have used fit for all of your analysis :-) and you can set number = Inf to include all features in your output table. For QA please see the very helpful limma user's guide and package arrayQualityMetrics. Generally, I'd try to include *all* arrays in your limma analysis instead of only the three you're interested in since that should improve your power -- but I just see that GSE37326 is actually using two different array platforms and that may complicate things... :-( Hope that helps, - axel On Tue, Jul 15, 2014 at 6:20 PM, Jeannette [guest] <guest@bioconductor.org> wrote: > I am an absolut beginner in R and limma. > I would like to analyze 2 colour microarray data (GSE37326): > normalization, quality control, estimate diff. genes > > I am only interested in finding diff. genes for one substance (slides: > GSM915419_NP_1, GSM915420_NP_2 and GSM915421_NP_3). > > targets.txt > SampleNumber FileName Cy3 Cy5 > 1 GSM915419_NP_1.txt DMSO NP > 2 GSM915420_NP_2.txt DMSO NP > 3 GSM915421_NP_3.txt DMSO NP > > > Is this correct for my files? > > targets <- readTargets("targets_test_.txt") > > RG <- read.maimages(targets, columns=list(R="F635 Median",G="F532 > Median",Rb="B635",Gb="B532")) > > MA <- normalizeWithinArrays(RG, method="loess") > > fit <- lmFit(MA) > > fit <- eBayes(fit) > > output <- topTable(fit2, adjust="BH", coef="NP", number=100000) > > write.table(output, file="NP_vs_DMSO_15072014.txt", sep="t", quote=FALSE) > > I am really not sure if the output table is correct (especially my use of > read.maimages?). > How to perform a ‘Quality assessment’ before and after normalization? > How to get gene annotation? > > Any feedback is very welcome. > Thanks and best regards, > Jeannette > > > -- output of sessionInfo(): > > R version 3.0.2 (2013-09-25) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 > [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C > [5] LC_TIME=German_Germany.1252 > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] limma_3.18.13 affy_1.40.0 Biobase_2.22.0 > BiocGenerics_0.8.0 > > loaded via a namespace (and not attached): > [1] affyio_1.30.0 BiocInstaller_1.12.1 preprocessCore_1.24.0 > [4] tools_3.0.2 zlibbioc_1.8.0 > R version 3.0.2 (2013-09-25) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 > [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C > [5] LC_TIME=German_Germany.1252 > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] limma_3.18.13 affy_1.40.0 Biobase_2.22.0 > BiocGenerics_0.8.0 > > loaded via a namespace (and not attached): > [1] affyio_1.30.0 BiocInstaller_1.12.1 preprocessCore_1.24.0 > [4] tools_3.0.2 zlibbioc_1.8.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Axel Klenk Research Informatician Information Management Drug Discovery Actelion Pharmaceuticals Ltd. • Gewerbestrasse 16 • CH-4123 Allschwil • Switzerland H91.O1.W01.2 axel.klenk@actelion.com • www.actelion.com Address for visitors: Hegenheimermattweg 91 -- The information of this email and in any file transmitted with it is strictly confidential and may be legally privileged. It is intended solely for the addressee. If you are not the intended recipient, any copying, distribution or any other use of this email is prohibited and may be unlawful. In such case, you should please notify the sender immediately and destroy this email. The content of this email is not legally binding unless confirmed by letter. Any views expressed in this message are those of the individual sender, except where the message states otherwise and the sender is authorised to state them to be the views of the sender's company. For further information about Actelion please see our website at http://www.actelion.com [[alternative HTML version deleted]]