Hallo everybody, I am running a microarray analysis using the miRNA2.0 arrays from affymetrix. I ran it a few times with different parameters and was wondering why I am getting different results in some cases but not in other. I than accidentally fond out that there is a strong different in the results I get when I am normalizing my data with RMA or with call.exprs( data, "rma") > eset.rma_miRNA= call.exprs(data, "rma") or > normData<-rma(data) Can anyone explain to me what is the difference between the two methods. In the help file from call.exprs they only say that it works with the rma algorithm, but no more. Should there be a difference in the results? Thanks a lot for the help Assa > sessionInfo() R version 2.13.0 (2011-04-13) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] tools tcltk splines stats graphics grDevices datasets utils methods base other attached packages: [1] mirna20cdf_2.8.0 mirna102xgaincdf_2.8.0 tkWidgets_1.30.0 DynDoc_1.30.0 widgetTools_1.30.0 [6] limma_3.8.2 siggenes_1.26.0 multtest_2.8.0 simpleaffy_2.28.0 gcrma_2.24.1 [11] genefilter_1.34.0 affy_1.30.0 Biobase_2.12.1 rcom_2.2-3.1 rscproxy_1.3-1 loaded via a namespace (and not attached): [1] affyio_1.20.0 annotate_1.30.0 AnnotationDbi_1.14.1 Biostrings_2.20.1 DBI_0.2-5 [6] IRanges_1.10.4 MASS_7.3-12 preprocessCore_1.14.0 RSQLite_0.9-4 survival_2.36-5 [11] xtable_1.5-6 [[alternative HTML version deleted]]

are you really sure that you're getting different results? all that call.exprs(obj, 'rma') does is to call rma(obj)... nothing else. make sure you don't have any pre-existing object on your R session. i'd be really surprised if both strategies give you discordant results... here's a reproducible example of what i mean: library(affydata) library(simpleaffy) data(Dilution) y1 = exprs(rma(Dilution)) y2 = exprs(call.exprs(Dilution, 'rma')) all.equal(y1, y2) ## i get TRUE, as expected b On 16 June 2011 11:41, Assa Yeroslaviz <frymor at="" gmail.com=""> wrote: > Hallo everybody, > > I am running a microarray analysis using the miRNA2.0 arrays from > affymetrix. > I ran it a few times with different parameters and was wondering why I am > getting different results in some cases but not in other. > > I than accidentally fond out that there is a strong different in the results > I get when I am normalizing my data with RMA ?or with call.exprs( data, > "rma") > >> eset.rma_miRNA= call.exprs(data, "rma") > > or > >> normData<-rma(data) > > Can anyone explain to me what is the difference between the two methods. In > the help file from call.exprs they only say that it works with the rma > algorithm, but no more. > > Should there be a difference in the results? > > Thanks a lot for the help > > Assa > >> sessionInfo() > R version 2.13.0 (2011-04-13) > Platform: i386-pc-mingw32/i386 (32-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 ?LC_CTYPE=English_United > States.1252 ? ?LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C ? ? ? ? ? ? ? ? ? ? ? ? ? LC_TIME=English_United > States.1252 > > attached base packages: > ?[1] tools ? ? tcltk ? ? splines ? stats ? ? graphics ?grDevices datasets > utils ? ? methods ? base > > other attached packages: > ?[1] mirna20cdf_2.8.0 ? ? ? mirna102xgaincdf_2.8.0 tkWidgets_1.30.0 > DynDoc_1.30.0 ? ? ? ? ?widgetTools_1.30.0 > ?[6] limma_3.8.2 ? ? ? ? ? ?siggenes_1.26.0 ? ? ? ?multtest_2.8.0 > simpleaffy_2.28.0 ? ? ?gcrma_2.24.1 > [11] genefilter_1.34.0 ? ? ?affy_1.30.0 ? ? ? ? ? ?Biobase_2.12.1 > rcom_2.2-3.1 ? ? ? ? ? rscproxy_1.3-1 > > loaded via a namespace (and not attached): > ?[1] affyio_1.20.0 ? ? ? ? annotate_1.30.0 ? ? ? AnnotationDbi_1.14.1 > Biostrings_2.20.1 ? ? DBI_0.2-5 > ?[6] IRanges_1.10.4 ? ? ? ?MASS_7.3-12 ? ? ? ? ? preprocessCore_1.14.0 > RSQLite_0.9-4 ? ? ? ? survival_2.36-5 > [11] xtable_1.5-6 > > ? ? ? ?[[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Successful people ask better questions, and as a result, they get better answers. (Tony Robbins)