If all the preprocessing you're doing to the Illumina chips is quantile normalization, you could use: normalize.quantiles.determine.target() followed by: normalize.quantiles.use.target() Both are in the preprocessCore package. Best, Matt On Sun, Apr 14, 2013 at 11:53 AM, Nathan Skene <nathan.skene at="" gmail.com=""> wrote: > Hi Matt, > > That looks like exactly the thing... but it wouldn't work on Illumina, > right? RMA is Affy only? > > Thanks, > > Nathan > > > On 14 April 2013 16:43, Matthew McCall <mccallm at="" gmail.com=""> wrote: >> >> Nathan, >> >> Take a look at the frma package and paper: >> McCall MN, Bolstad BM, and Irizarry RA* (2010). Frozen Robust >> Multi-Array Analysis (fRMA), Biostatistics, 11(2):242-253. >> >> Best, >> Matt >> >> >> >> On Sun, Apr 14, 2013 at 10:40 AM, Nathan Skene [guest] >> <guest at="" bioconductor.org=""> wrote: >> > >> > Hi, >> > >> > I have a built a classifier on a set of my own microarray data. >> > >> > I would like to be able to show that it works on new data, by taking >> > some from GEO (same tissue, same array platform etc) and classifying that. >> > >> > However, the probe values in the new datasets are offset compared to >> > those in my original dataset, presumably because of differences in how they >> > were normalised. >> > >> > Is there a way to normalize datasets taken from GEO so that they are >> > normalized with respect to an existing dataset? >> > >> > Thanks >> > >> > >> > -- output of sessionInfo(): >> > >> > - >> > >> > -- >> > Sent via the guest posting facility at bioconductor.org. >> > >> > _______________________________________________ >> > 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 >> >> >> >> -- >> Matthew N McCall, PhD >> 112 Arvine Heights >> Rochester, NY 14611 >> Cell: 202-222-5880 > > -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880