Hello! I am using the vsn package to process Rat Gene 2.0 ST chips. I have to export the data from xps and put the data into vsn as a matrix. The data going into vsn has column names corresponding to "X" and "Y" locations and the MEAN intensity for each sample. I call vsn with ' fit <- vsn2(as.matrix(data[,3:ncol(data)]))' which is then followed by the prediction step 'n_data <- predict(fit, newdata=as.matrix(data[,3:ncol(data)]))' Now the output data has no "X" or "Y" values and the row numbers start at 660693. What is the standard method for keeping a unique identifier for each row name throughout the vsn algorithm? TIA Matt

Hi Matthew, in the below, the ?predict? step is not needed. You can simply use 'exprs(fit)?, and this matrix should have the same shape and the same row names as the one you inserted into vsn2. HTH, Wolfgang Il giorno 07 Mar 2014, alle ore 00:25, Thornton, Matthew <matthew.thornton at="" med.usc.edu=""> ha scritto: > Hello! > > I am using the vsn package to process Rat Gene 2.0 ST chips. I have to export the data from xps and put the data into vsn as a matrix. The data going into vsn has column names corresponding to "X" and "Y" locations and the MEAN intensity for each sample. > > I call vsn with ' fit <- vsn2(as.matrix(data[,3:ncol(data)]))' which is then followed by the prediction step 'n_data <- predict(fit, newdata=as.matrix(data[,3:ncol(data)]))' > > Now the output data has no "X" or "Y" values and the row numbers start at 660693. What is the standard method for keeping a unique identifier for each row name throughout the vsn algorithm? > > TIA > > Matt > _______________________________________________ > 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