Dear list, I am running snapCGH (1.4.0) in R 2.5.1 on a sun-solaris2.9 with 25 Agilent mouse 244K CGH arrays. I run the processCGH function for 2 days, and before I get this job done, the program just froze and quit without giving me any result. If I only run two arrays at a time, it takes about 1.5 hour to run the processCGH function, and about another 1.5 hours to run the runDNAcopy function. Are there any ways to speed up these two steps? Thanks, Caimiao my code lines: MA2<-processCGH(MA1, method.of.averaging=mean, ID='ProbeName',maxChromThreshold = 24) SegInfo.DNAcopy<-runDNAcopy(MA2) > sessionInfo() R version 2.5.1 (2007-06-27) sparc-sun-solaris2.9 locale: C attached base packages: [1] "splines" "grid" "tools" "stats" "graphics" "grDevices" [7] "utils" "datasets" "methods" "base" other attached packages: xtable snapCGH aCGH sma multtest cluster "1.4-6" "1.4.0" "1.10.0" "0.5.15" "1.16.0" "1.11.7" GLAD aws DNAcopy tilingArray pixmap geneplotter "1.10.0" "1.3-3.1" "1.10.0" "1.14.0" "0.4-7" "1.14.0" lattice annotate genefilter survival vsn strucchange "0.15-11" "1.14.1" "1.14.1" "2.32" "2.2.0" "1.3-2" sandwich zoo RColorBrewer affy affyio Biobase "2.0-2" "1.3-2" "1.0-1" "1.14.2" "1.4.1" "1.14.1" limma "2.10.5"

Hi Caimiao, For me, the DNAcopy segmentation function ran quicker in the actually DNAcopy package than it did in the snapCGH package, not sure why but I do know they made some speed improvements in the CBS algorithm that may not have been implemented in snapCGH. It may be worth investigating using the actual DNAcopy package, especially if snapCGH is crashing on you. If anyone feels this is wrong feel to correct me, just thought I should contribute as I've made heavy use of this mailing list myself! Regards John Quoting caiwei at mdanderson.org on Fri 05 Oct 2007 17:46:58 BST: > > Dear list, > > I am running snapCGH (1.4.0) in R 2.5.1 on a sun-solaris2.9 with 25 > Agilent > mouse 244K CGH arrays. I run the processCGH function for 2 days, > and > before I get this job done, the program just froze and quit without > giving > me any result. If I only run two arrays at a time, it takes about > 1.5 > hour to run the processCGH function, and about another 1.5 hours to > run the > runDNAcopy function. > > Are there any ways to speed up these two steps? > > Thanks, > > Caimiao > > > my code lines: > MA2<-processCGH(MA1, method.of.averaging=mean, > ID='ProbeName',maxChromThreshold = 24) > SegInfo.DNAcopy<-runDNAcopy(MA2) > > > sessionInfo() > R version 2.5.1 (2007-06-27) > sparc-sun-solaris2.9 > > locale: > C > > attached base packages: > [1] "splines" "grid" "tools" "stats" "graphics" > "grDevices" > [7] "utils" "datasets" "methods" "base" > > other attached packages: > xtable snapCGH aCGH sma multtest > cluster > "1.4-6" "1.4.0" "1.10.0" "0.5.15" "1.16.0" > "1.11.7" > GLAD aws DNAcopy tilingArray pixmap > geneplotter > "1.10.0" "1.3-3.1" "1.10.0" "1.14.0" "0.4-7" > "1.14.0" > lattice annotate genefilter survival vsn > strucchange > "0.15-11" "1.14.1" "1.14.1" "2.32" "2.2.0" > "1.3-2" > sandwich zoo RColorBrewer affy affyio > Biobase > "2.0-2" "1.3-2" "1.0-1" "1.14.2" "1.4.1" > "1.14.1" > limma > "2.10.5" > > _______________________________________________ > 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 >