problem to obtain exprset using GEOquery
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@alberto-goldoni-711
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@stephen-henderson-71
Last seen 7.0 years ago
You can't. The information in the GSE object and the exprSet object contain probeset summary data i.e the summary of 11 probes into 1 probeset value. rma uses all probes to create a probeset summary too. You need the CEL files and only some GEO entries supply these-- although occasionally the SOFT files contain rma data already. Stephen Henderson Wolfson Inst. for Biomedical Research Cruciform Bldg., Gower Street University College London United Kingdom, WC1E 6BT +44 (0)207 679 6827 -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Alberto Goldoni Sent: 13 July 2006 11:19 To: bioconductor at stat.math.ethz.ch Subject: [BioC] problem to obtain exprset using GEOquery I have converted a GSE object to an exprSet object "eset2" just in the vignette but I wanna analyze microarray dataset again for example with: usually starting from CEL files i should edit: data<-ReadAffy(widget=T) pData(data) and then: data.rma<-rma(data) # for example! BUT STARTING FROM THE exprSet object "eset2" HOW CAN PROCEDE IN ORDER TO reanalyze microarray if i write: eset2.rma<-rma(eset2) Errore in probeNames(object, subset) : no direct or inherited method for function 'probeNames' for this call where > eset2 Expression Set (exprSet) with 22283 genes 76 samples phenoData object with 1 variables and 76 cases varLabels : samples how can I do to create an affybatch object in order to use rma function on my dataset? ps: to obtain eset2 I have followed the instruction on the GEOquery vignette: > probesets <- Table(GPLList(gse)[[1]])$ID > data.matrix <- log2(do.call("cbind", lapply(GSMList(gse), function(x) { + tab <- Table(x) + mymatch <- match(probesets, tab$ID_REF) + return(tab$VALUE[mymatch]) + }))) > rownames(data.matrix) <- probesets > colnames(data.matrix) <- names(GSMList(gse)) > pdata <- data.frame(samples = names(GSMList(gse))) > rownames(pdata) <- names(GSMList(gse)) > pheno <- new("phenoData", pData = pdata, varLabels = as.list("samples")) > eset2 <- new("exprSet", exprs = data.matrix, phenoData = pheno) > eset2 Dr Alberto Goldoni Medical Genetics Unit S. Orsola-Malpighi Hospital Via Massarenti n.9, Pad 11 40100 Bologna, Italy Mobile Phone: 338-4145970 Fax: 051-636-4004 <mailto:alberto.goldoni at="" eurogene.org=""> alberto.goldoni at eurogene.org <http: www.eurogene.org=""> www.eurogene.org <http: www.lagem.it=""> www.lagem.it [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ********************************************************************** This email and any files transmitted with it are confidentia...{{dropped}}
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Stephen Henderson wrote: > You can't. The information in the GSE object and the exprSet object > contain probeset summary data i.e the summary of 11 probes into 1 > probeset value. rma uses all probes to create a probeset summary too. > You need the CEL files and only some GEO entries supply these-- although > occasionally the SOFT files contain rma data already. Just to clarify, the algorithm for doing this would be something like: 1) Use GEOquery to process the GSE file using getGEO followed by a little manipulation to obtain an exprSet. This exprSet contains summarized data (and the summary method varies from GSE to GSE). 2) From the GEO website, look to see if raw data is available. If it is, it will often contain the .CEL files. If that is the case, then download the files and process using RMA (or whatever method you like). The .CEL files will be named with something like GSMXXXX.CEL. The GSMXXXX part should typically match the GSMXXXX in the exprSet from the getGEO parsing. So, if you are careful about the order, you can replace the exprs() slot of the first exprSet with the exprs() slot from the second exprSet. Then, you will have all the phenodata from the GSE, but with the expression values from your own analyses. Sean
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