Hi Steve and James, Thanks for pointing me to the proper direction. For the archive (in case someone has the same question): First normalize: affy.data <- ReadAffy() x.norm <- rma(affy.data) y <- exprs(x.norm) To mean center and scale the (normalized) dataset: yscaled <- t(scale(t(y))) This returns a dataset (yscaled) which is *mean* centered and has a standard deviation of one (unit variance normalized; hear *mean*=0, SD=1)). Source: excellent site of Dr Girke: http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#clustering_ prepro For *median* centering + scaling: #1st: perform median centering: y <- apply(y,1,function( x){ x-median(x) }) #Note: 1=row, 2=column #2nd: unit variance normalization (here *median*=0, SD=1) yscaled <- t(scale(t(y),center=FALSE)) Regards, Guido --------------------------------------------------------- Guido Hooiveld, PhD Nutrition, Metabolism & Genomics Group Division of Human Nutrition Wageningen University Biotechnion, Bomenweg 2 NL-6703 HD Wageningen the Netherlands tel: (+)31 317 485788 fax: (+)31 317 483342 email: guido.hooiveld at wur.nl internet: http://nutrigene.4t.com http://www.researcherid.com/rid/F-4912-2010 -----Original Message----- From: Steve Lianoglou [mailto:mailinglist.honeypot@gmail.com] Sent: Monday, July 11, 2011 15:25 To: Hooiveld, Guido Cc: bioconductor (bioconductor at stat.math.ethz.ch) Subject: Re: [BioC] package/function for median center & unit variance Hi Guido, On Mon, Jul 11, 2011 at 9:17 AM, Hooiveld, Guido <guido.hooiveld at="" wur.nl=""> wrote: > Dear list, > > After (RMA) normalization I would like to post-process my array data for downstream analyses by means of median centering and/or unit variance normalization. > Does anyone know a library that contains these functions? > Using available functions would minimize the chance on errors due my limited R coding skills... ;) I had a look at the library Genefilter but it doesn't contain these functions. The base `scale` function will get yo close to where you want to be. It works on a matrix, so you'll have to get your `exprs` matrix out of your RMA normalized data. By default, `scale` actually does mean-centering and then divides the columns by their std.dev. The help page for `scale` will also point you to `sweep` which has an example of how to median center the columns of a matrix. HTH, -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology ?| Memorial Sloan-Kettering Cancer Center ?| Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact