Question: affy - Anotation of Afymetrix PrimeView chipe
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6.1 years ago by
Dear all I am a ner person in analyzing microarrays with R. I ma working on dataset GSE41960. As far as I know RMA method summarises probes into genes, hoverer when I run limma and use topTable I have probe ID instead of gene names. Where in the pipeline I should merge the probes ? The second question is about CDF file. I know these are file used for description and mapping of the probes. But I did not figured out how to use it with affy and limma. I am familiar with user guide for affy and limma. Many thanks in advance -- Adam Olejnik Department of Human Molecular Genetics University of Adam Mickiewicz 61-614 Poznañ tel. +4861 829-58-33 http://www.lhmg.amu.edu.pl/ [[alternative HTML version deleted]]
cdf probe affy limma • 1.7k views
modified 6.1 years ago by James W. MacDonald51k • written 6.1 years ago by Adam Olejnik10
Answer: affy - Anotation of Afymetrix PrimeView chipe
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6.1 years ago by
United States
James W. MacDonald51k wrote:
Hi Adam, On Wednesday, October 23, 2013 10:44:34 AM, Adam Olejnik wrote: > Dear all > I am a ner person in analyzing microarrays with R. > I ma working on dataset GSE41960. > As far as I know RMA method summarises probes into genes, hoverer when I > run limma and use topTable I have probe ID instead of gene names. > Where in the pipeline I should merge the probes ? As you note, RMA summarizes probes, but not into genes, but into probesets. Probesets are intended to interrogate transcripts, which are certainly not genes. However, most people end up collapsing transcripts back to gene IDs, so maybe that is not relevant. But to answer your question, you summarize when you run rma(). I am assuming you are doing something like library(affy) dat <- ReadAffy() eset <- rma(dat) In which case the ExpressionSet object called 'eset' now contains the summarized data, and limma knows what to do with it. So if you fit a model and end up with an MArrayLM object fit <- lmFit(eset, design) fit2 <- contrasts.fit(fit, contrast) fit2 <- eBayes(fit2) You can then annotate these data using a primeview.db package. But note that there isn't such a thing on the BioC website. It doesn't really matter, as it is simple to create using the AnnotationForge package. All you need to do is go to the Affy website, and get the primeview annotation csv file http://www.affymetrix.com/Auth/analysis/downloads/na32/ivt/PrimeView.n a32.annot.csv.zip Install AnnotationDbi and the human.db0 packages, and then do what I recommend here: https://stat.ethz.ch/pipermail/bioconductor/attachments/20130711/7e4d7 7fb/attachment.pl You can then do install.packages("primeview.db", type="source", repos=NULL) and then library(primeview.db) gns <- select(primeview.db, featureNames(eset), c("SYMBOL","GENENAME")) and if you don't get an error about 1 to many mappings you can do fit2$genes <- gns otherwise you can be super naive and just take the first mapping available fit2$genes <- gns[!duplicated(gns[,1]),] and then topTable(fit, coef=1) will have annotated genes in it. > > The second question is about CDF file. I know these are file used for > description and mapping of the probes. But I did not figured out how to use > it with affy and limma. This happens automatically. Best, Jim > > I am familiar with user guide for affy and limma. > > Many thanks in advance > > > > > _______________________________________________ > 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 -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099