You can also use R package aroma.affymetrix: http://groups.google.com/group/aroma-affymetrix/ It is cross platform and you should be able to process any number of arrays with roughly 1-2GB of RAM. All you need is CEL files and a CDF file. Cheers Henrik On 11/14/07, Michal Blazejczyk <michal.blazejczyk at="" mail.mcgill.ca=""> wrote: > Hi, > > Yeah, typical... > > Try using function just.rma instead of calling ReadAffy. > just.rma operates directly on files and requires way less > memory. > > Or run it on Linux, I think there's less memory issues > there. > > Good luck, > > Best, > Michal Blazejczyk > FlexArray Lead Developer > http://genomequebec.mcgill.ca/FlexArray/ > > > > Hello~~~ > > > > > > > > I am trying to read 80 HG-U133A arrays so I did as follows: > > > > > > > >> memory.limit(size=4095) > > > >> options(object.size=10000000000, digits=8, scipen=100, > >> memory=3200483647, contrasts=c("contr.treatment", "contr.poly")) > > > >> library(affy) > > > >> cel.file <- ReadAffy(celfile.path = ??D://CEL) > > > > > > > > However, it showed > > > > > > > > Error: cannot allocate vector of size 309.4 Mb > > > > > > > > I have tried adding the --max-mem-size=2Gb tag onto my shortcut. > > > > The machine has 2G RAM and a 3.30GHz processor. > > > > Is there any idea to let R use more memory anywhere? > > > > Thank you~ > > > > > > > > Best Regards, > > > > Pure > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >

Oscar, I am curious how long it runs and the configuration of the linux cluster. weiwei On 11/17/07, olsen <olsen2002 at="" yahoo.com=""> wrote: > > > > > Hello~~~ > > > > > > > > I am trying to read 80 HG-U133A arrays so I did as > > follows: > > > > > > > > > memory.limit(size=4095) > > > > > options(object.size=10000000000, digits=8, > > scipen=100, memory=3200483647, > > contrasts=c("contr.treatment", "contr.poly")) > > > > > library(affy) > > > > > cel.file <- ReadAffy(celfile.path = ??D://CEL) > > > > > > > > However, it showed > > > > > > > > Error: cannot allocate vector of size 309.4 Mb > > > > > > > > I have tried adding the --max-mem-size=2Gb tag onto > > my shortcut. > > > > The machine has 2G RAM and a 3.30GHz processor. > > > > Is there any idea to let R use more memory anywhere? > > > > Thank you~ > > > > > > > > Best Regards, > > > > Pure > > > Pure, > > My advice: run them in Linux. We have run up to 1000 > arrays in a linux cluster. > > Oscar Puig > > > > > _____________________________________________ > > Bioconductor mailing list > > Bioconductor at stat.math.ethz.ch > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > ______________________________________________________________ ______________________ > Never miss a thing. Make Yahoo your home page. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Pure, The error message tells that at *some point in time* during the execution of "ReadAffy" a vector of given size cannot be allocated because there is not enough memory free on your system. This does not mean that you R session cannot handle anything larger than 309.4 Mb. To check how much memory is currently used by your session, you can call the garbage collector ("gc()", a side-effect is that the memory used will be printed. It is also a good idea to monitor what other processes on your machine are using significant amounts of memory. So to get R use more memory, the obvious is to get more RAM (nowadays, 2Gb is getting quickly limiting) and if get a lot more than 2Gb make sure that your OS/hardware are capable of making use of it. If you are only planning to process your data with RMA, the function "justRMA" is using tricks to use less memory, and should do the job on a system with 2Gb. If you really want to look at probe-level data with that much memory, there are other strategies but they will currently require extra efforts (I think). Hoping this helps, Laurent > >> >> Hello~~~ >> >> >> >> I am trying to read 80 HG-U133A arrays so I did as >> follows: >> >> >> >> > memory.limit(size=4095) >> >> > options(object.size=10000000000, digits=8, >> scipen=100, memory=3200483647, >> contrasts=c("contr.treatment", "contr.poly")) >> >> > library(affy) >> >> > cel.file <- ReadAffy(celfile.path = ??D://CEL) >> >> >> >> However, it showed >> >> >> >> Error: cannot allocate vector of size 309.4 Mb >> >> >> >> I have tried adding the --max-mem-size=2Gb tag onto >> my shortcut. >> >> The machine has 2G RAM and a 3.30GHz processor. >> >> Is there any idea to let R use more memory anywhere? >> >> Thank you~ >> >> >> >> Best Regards, >> >> Pure >> > Pure, > > My advice: run them in Linux. We have run up to 1000 > arrays in a linux cluster. > > Oscar Puig > > > > > _____________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > ______________________________________________________________ ______________________ > Never miss a thing. Make Yahoo your home page. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor >