Hello everybody, I wanted to use rMAT for some of my ChIP-chip analysis and tried to follow the tutorial (http://wiki.rglab.org/index.php? title=Public:RMAT). I have updated everything (R version 2.11.0 and rMAT version 2.4.0) and have downloaded the tutorial data file (EM). I have managed to do everything up to the rbind part. I have the same summary as in the tutorial (summary(ER)), but as soon as I try to normalize the data, my R crashes. I am wondering if any of you have experienced similar outcomes? Could the amount of processing be too large? Has any of you been able to successfully follow the tutorial? Thanks for any useful help, Patrick R version 2.11.0 (2010-04-22) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R est un logiciel libre livr? sans AUCUNE GARANTIE. Vous pouvez le redistribuer sous certaines conditions. Tapez 'license()' ou 'licence()' pour plus de d?tails. R est un projet collaboratif avec de nombreux contributeurs. Tapez 'contributors()' pour plus d'information et 'citation()' pour la fa?on de le citer dans les publications. Tapez 'demo()' pour des d?monstrations, 'help()' pour l'aide en ligne ou 'help.start()' pour obtenir l'aide au format HTML. Tapez 'q()' pour quitter R. [R.app GUI 1.32 (5573) i386-apple-darwin9.8.0] > library(rMAT) Le chargement a n?cessit? le package : IRanges Attachement du package : 'IRanges' The following object(s) are masked from 'package:base': cbind, Map, mapply, order, paste, pmax, pmax.int, pmin, pmin.int, rbind, rep.int, table Le chargement a n?cessit? le package : Biobase Welcome to Bioconductor Vignettes contain introductory material. To view, type 'openVignette()'. To cite Bioconductor, see 'citation("Biobase")' and for packages 'citation(pkgname)'. Attachement du package : 'Biobase' The following object(s) are masked from 'package:IRanges': updateObject Le chargement a n?cessit? le package : affxparser > bpmapA<-"P1_CHIP_A.Anti-Sense.hs.NCBIv35.NR.bpmap" > celA<-c("MCF_ER_A1.CEL","MCF_ER_A3.CEL", "MCF_ER_A4.CEL", "MCF_INP_A1.CEL", "MCF_INP_A3.CEL","MCF_INP_A4.CEL") > ERA<-BPMAPCelParser(bpmapA, celA, seqName="chr2") > bpmapB<-"P1_CHIP_B.Anti-Sense.hs.NCBIv35.NR.bpmap" > celB<-c("MCF_ER_B1.CEL","MCF_ER_B3.CEL", "MCF_ER_B4.CEL", "MCF_INP_B1.CEL", "MCF_INP_B3.CEL","MCF_INP_B4.CEL") > ERB<-BPMAPCelParser(bpmapB, celB, seqName="chr2") > bpmapC<-"P1_CHIP_C.Anti-Sense.hs.NCBIv35.NR.bpmap" > celC<-c("MCF_ER_C1.CEL","MCF_ER_C3.CEL", "MCF_ER_C4.CEL", "MCF_INP_C1.CEL", "MCF_INP_C3.CEL","MCF_INP_C4.CEL") > ERC<-BPMAPCelParser(bpmapC, celC, seqName="chr2") > > > ER<-rbind(ERA,ERB,ERC) > > summary(ER) Genome interrogated: P1_CHIP_A.Anti-Sense.hs.NCBIv35.NR P1_CHIP_B.Anti-Sense.hs.NCBIv35.NR P1_CHIP_C.Anti-Sense.hs.NCBIv35.NR Chromosome(s) interrogated: chr21, chr22 Sample name(s): MCF_ER_A1 MCF_ER_A3 MCF_ER_A4 MCF_INP_A1 MCF_INP_A3 MCF_INP_A4 The total number of probes is: 1015922 Preprocessing Information - Transformation: log - Normalization: none

Hi, On Tue, Apr 27, 2010 at 11:01 AM, Patrick Schorderet <patrick.schorderet at="" epfl.ch=""> wrote: > > Hello everybody, > > I wanted to use rMAT for some of my ChIP-chip analysis and tried to follow > the tutorial (http://wiki.rglab.org/index.php?title=Public:RMAT). I have > updated everything (R version 2.11.0 and rMAT version 2.4.0) and have > downloaded the tutorial data file (EM). I have managed to do everything up > to the rbind part. I have the same summary as in the tutorial (summary(ER)), > but as soon as I try to normalize the data, my R crashes. I am wondering if > any of you have experienced similar outcomes? Could the amount of processing > be too large? Has any of you been able to successfully follow the tutorial? I don't know what you mean by "crash", but: I tried to run it on my machine. I'm not sure if it's crashing, but the call to `ERnorm<-NormalizeProbes(ER, method="PairBinned",robust=TRUE)` pegs a CPU @ 100% for a long while and doesn't return after what I think has been at least 20 mins, or so (I've killed the process). For the record, I'm running 64bit R on a Mac Pro with 8 GB of RAM. I noticed that you are running 32bit R and the memory of the pegged R process is upwards of 2GB (1.9GB to be exact). Since 32bit R is stuck with dealing with 2GB of RAM at a stretch, perhaps this might be one of the problems you are facing. So ... if you do have a 64bit system with enough memory, perhaps you can try running R in 64bit mode (use R64.app if you want to use the GUI) to see if the normalization step ever finishes. The versions of our packages should be the same since I just updated to R 2.11 (release) yesterday and updated all packages along with it. -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

Sorry for the lack of precision in my previous post. What I meant by 'crashes' is that in my Force Quit Application, I have a little "(not responding)" next to my R. I have tried to work with R64 but this doesn't help either. Am I really gonna have to buy a new computer...? Thanks for the help, Patrick