Bioconductor Fellows, I have 8 samples (affy arrays with 22,690 probesets). I would like to: 1. Remove outliers and select some genes (using raw signal data from *.CEL files), to then 2. Run the standard data processing technique (let say just RMA) Obviously I have problems on doing these. I have used these R commands: *******************Begin R commands********************** Data <- ReadAffy() exprmatf=exprs(Data) dim(exprmatf) # Floor & ceiling of raw data exprmatf [exprmatf <10] <-10 exprmatf [exprmatf >25000]<-25000 # Preliminary selection of genes tmp1<-apply(exprmatf,1,max) tmp2<-apply(exprmatf,1,min) which1<-(1:506944)[(tmp1/tmp2)>2] which2<-(1:506944)[(tmp1-tmp2)>100] exprmatf.sub <-intersect(which1,which2) exprmatfilt <-exprmatf[exprmatf.sub,] Dataf<- write.table(exprmatfilt) library(vsn) normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "vsn") esetf <- expresso(Dataf, bg.correct=FALSE, normalize.method="vsn", pmcorrect.method="pmonly", summary.method="medianpolish") *******************End R commands********************** The last command does not run! I got this error message: normalization: vsn PM/MM correction : pmonly expression values: medianpolish normalizing...Error in normalize(afbatch, normalize.method) : No direct or inherited method for function "normalize" for this call I would appreciate somebody indicating why is that? Or what I am doing wrong. Thank you very much for the help!! Roger Roger L. Vallejo, Ph.D. Assist. Professor of Genomics & Bioinformatics Genomics & Bioinformatics Laboratory Department of Dairy & Animal Science The Pennsylvania State University 305 Henning Building University Park, PA 16802 Phone: (814) 865-1846 Email: rvallejo@psu.edu [[alternative HTML version deleted]]

The error you are getting is due to the fact that Dataf <- write.table(exprmatfilt) doesn't create any R object, so when you run expresso, you are passing a NULL object for an AffyBatch. In addition, I am not sure that what you are trying to do is going to work. There are at least two problems here. First, you would need to pass exprmatfilt back into Data (exprs(Data) <- exprmatfilt), however, if you pass a smaller matrix back into an AffyBatch it will mess things up. > dat <- read.affybatch(filenames=list.celfiles()) > dat2 <- dat > exprmat <- exprs(dat) > exprs(dat2) <- exprmat[-(100:150),] > all.equal(pm(dat2, geneNames(dat2)[1]), pm(dat, geneNames(dat)[1])) [1] "Mean relative difference: 3.187727" > geneNames(dat2)[1] [1] "1007_s_at" > geneNames(dat)[1] [1] "1007_s_at" So passing the smaller matrix back into the AffyBatch changes what data are attributed to a given gene. The second problem is that you are randomly subsetting the raw data, but you are not making any changes to the cdfenv to accommodate these changes. When you run expresso, the cdfenv is used to get all the probe data for each gene. However, you are removing some of the expression values for certain genes without telling the cdfenv which genes have lost data. What will happen is that you will end up with probes from different probesets used to compute expression values for a given gene. So, long story short, you should not be doing any of this. Medianpolish will not be affected by these 'outlier' data that you are removing anyway. HTH, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> "Roger Vallejo" <rvallejo@psu.edu> 06/11/04 02:08PM >>> Bioconductor Fellows, I have 8 samples (affy arrays with 22,690 probesets). I would like to: 1. Remove outliers and select some genes (using raw signal data from *.CEL files), to then 2. Run the standard data processing technique (let say just RMA) Obviously I have problems on doing these. I have used these R commands: *******************Begin R commands********************** Data <- ReadAffy() exprmatf=exprs(Data) dim(exprmatf) # Floor & ceiling of raw data exprmatf [exprmatf <10] <-10 exprmatf [exprmatf >25000]<-25000 # Preliminary selection of genes tmp1<-apply(exprmatf,1,max) tmp2<-apply(exprmatf,1,min) which1<-(1:506944)[(tmp1/tmp2)>2] which2<-(1:506944)[(tmp1-tmp2)>100] exprmatf.sub <-intersect(which1,which2) exprmatfilt <-exprmatf[exprmatf.sub,] Dataf<- write.table(exprmatfilt) library(vsn) normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "vsn") esetf <- expresso(Dataf, bg.correct=FALSE, normalize.method="vsn", pmcorrect.method="pmonly", summary.method="medianpolish") *******************End R commands********************** The last command does not run! I got this error message: normalization: vsn PM/MM correction : pmonly expression values: medianpolish normalizing...Error in normalize(afbatch, normalize.method) : No direct or inherited method for function "normalize" for this call I would appreciate somebody indicating why is that? Or what I am doing wrong. Thank you very much for the help!! Roger Roger L. Vallejo, Ph.D. Assist. Professor of Genomics & Bioinformatics Genomics & Bioinformatics Laboratory Department of Dairy & Animal Science The Pennsylvania State University 305 Henning Building University Park, PA 16802 Phone: (814) 865-1846 Email: rvallejo@psu.edu [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor