I am having some problems getting these three flavors of gcrma to agree. The 1.0.0 vs 1.0.6 has the best agreement. However, 1.0.6 vs justGCRMA.1.0.6 has no agreement. If someone would please look at my code I used to compare these and see if I am doing something wrong with the justGCRMA calls, I would be eternally grateful. # gcrma 1.0.0 R 1.8.1 Patched (2004-03-23) mydata.raw <- ReadAffy(filenames=list.celfiles()) mydata.gcrma.1.0.0 <- gcrma(mydata.raw) # gcrma 1.0.6 R 1.9.0 beta (2004-03-27) mydata.raw.1.0.6 <- ReadAffy(filenames=list.celfiles()) mydata.gcrma.1.0.6 <- gcrma(mydata.raw.1.0.6, affinity.info = NULL, type = "fullmodel", fast = TRUE) mydata.justgcrma.1.0.6.memory <- justGCRMA(filenames=list.celfiles(), type="fullmodel", optimize.by="memory", fast = TRUE) mydata.justgcrma.1.0.6.speed <- justGCRMA(filenames=list.celfiles(), type="fullmodel", optimize.by="speed", fast = TRUE) # par(mfrow=c(2,2)) plot(exprs(mydata.gcrma.1.0.0)[,1],exprs(mydata.gcrma.1.0.6)[,1],main= "gcrma.1.0.0 vs gcrma.1.0.6") plot(exprs(mydata.gcrma.1.0.0)[,1],exprs(mydata.justgcrma.1.0.6.memory )[,1],main="gcrma.1.0.0 vs justGCRMA.1.0.6.memory") plot(exprs(mydata.gcrma.1.0.6)[,1],exprs(mydata.justgcrma.1.0.6.memory )[,1],main="gcrma.1.0.6 vs justGCRMA.1.0.6.memory") plot(exprs(mydata.justgcrma.1.0.6.memory)[,1],exprs(mydata.justgcrma.1 .0.6.speed)[,1],main="justGCRMA.1.0.6.memory vs justGCRMA.1.0.6.speed") # mydata.raw AffyBatch object size of arrays=640x640 features (64005 kb) cdf=MG_U74Av2 (12488 affyids) number of samples=20 number of genes=12488 annotation=mgu74av2 # R 1.9.0 beta package versions base 1.9.0 utils 1.9.0 graphics 1.9.0 stats 1.9.0 methods 1.9.0 gcrma 1.0.6 affy 1.4.21 Biobase 1.4.10 tools 1.9.0 xtable 1.2-1 splines 1.9.0 matchprobes 1.0.2 mgu74av2cdf 1.4.3 mgu74av2probe 1.0 # R 1.8.1patched package versions base 1.8.1 ts 1.8.1 nls 1.8.1 modreg 1.8.1 mva 1.8.1 ctest 1.8.1 methods 1.8.1 affy 1.3.28 eda 1.8.1 Biobase 1.4.0 reposTools 1.3.6 MASS 7.1-11 gcrma 1.0.0 xtable 1.2-2 annaffy 1.0.3 GO 1.5.0 KEGG 1.5.0 mgu74av2 1.4.0 mgu74av2cdf 1.4.3 mgu74av2probe 1.0 matchprobes 1.0.0 Thanks very much for any help or ideas, Dick ********************************************************************** ********* Richard P. Beyer, Ph.D. University of Washington Tel.:(206) 616 7378 Env. & Occ. Health Sci. , Box 354695 Fax: (206) 685 4696 4225 Roosevelt Way NE, # 100 Seattle, WA 98105-6099 http://depts.washington.edu/ceeh/ServiceCores/FC5/FC5.html

I can take a look at this on Monday when I am back in the lab. I don't see anything offhand that looks like it should give different results. Best, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> Dick Beyer <dbeyer@u.washington.edu> 04/09/04 5:06 PM >>> I am having some problems getting these three flavors of gcrma to agree. The 1.0.0 vs 1.0.6 has the best agreement. However, 1.0.6 vs justGCRMA.1.0.6 has no agreement. If someone would please look at my code I used to compare these and see if I am doing something wrong with the justGCRMA calls, I would be eternally grateful. # gcrma 1.0.0 R 1.8.1 Patched (2004-03-23) mydata.raw <- ReadAffy(filenames=list.celfiles()) mydata.gcrma.1.0.0 <- gcrma(mydata.raw) # gcrma 1.0.6 R 1.9.0 beta (2004-03-27) mydata.raw.1.0.6 <- ReadAffy(filenames=list.celfiles()) mydata.gcrma.1.0.6 <- gcrma(mydata.raw.1.0.6, affinity.info = NULL, type = "fullmodel", fast = TRUE) mydata.justgcrma.1.0.6.memory <- justGCRMA(filenames=list.celfiles(), type="fullmodel", optimize.by="memory", fast = TRUE) mydata.justgcrma.1.0.6.speed <- justGCRMA(filenames=list.celfiles(), type="fullmodel", optimize.by="speed", fast = TRUE) # par(mfrow=c(2,2)) plot(exprs(mydata.gcrma.1.0.0)[,1],exprs(mydata.gcrma.1.0.6)[,1],main= "gcrma.1.0.0 vs gcrma.1.0.6") plot(exprs(mydata.gcrma.1.0.0)[,1],exprs(mydata.justgcrma.1.0.6.memory )[,1],main="gcrma.1.0.0 vs justGCRMA.1.0.6.memory") plot(exprs(mydata.gcrma.1.0.6)[,1],exprs(mydata.justgcrma.1.0.6.memory )[,1],main="gcrma.1.0.6 vs justGCRMA.1.0.6.memory") plot(exprs(mydata.justgcrma.1.0.6.memory)[,1],exprs(mydata.justgcrma.1 .0.6.speed)[,1],main="justGCRMA.1.0.6.memory vs justGCRMA.1.0.6.speed") # mydata.raw AffyBatch object size of arrays=640x640 features (64005 kb) cdf=MG_U74Av2 (12488 affyids) number of samples=20 number of genes=12488 annotation=mgu74av2 # R 1.9.0 beta package versions base 1.9.0 utils 1.9.0 graphics 1.9.0 stats 1.9.0 methods 1.9.0 gcrma 1.0.6 affy 1.4.21 Biobase 1.4.10 tools 1.9.0 xtable 1.2-1 splines 1.9.0 matchprobes 1.0.2 mgu74av2cdf 1.4.3 mgu74av2probe 1.0 # R 1.8.1patched package versions base 1.8.1 ts 1.8.1 nls 1.8.1 modreg 1.8.1 mva 1.8.1 ctest 1.8.1 methods 1.8.1 affy 1.3.28 eda 1.8.1 Biobase 1.4.0 reposTools 1.3.6 MASS 7.1-11 gcrma 1.0.0 xtable 1.2-2 annaffy 1.0.3 GO 1.5.0 KEGG 1.5.0 mgu74av2 1.4.0 mgu74av2cdf 1.4.3 mgu74av2probe 1.0 matchprobes 1.0.0 Thanks very much for any help or ideas, Dick ********************************************************************** ********* Richard P. Beyer, Ph.D. University of Washington Tel.:(206) 616 7378 Env. & Occ. Health Sci. , Box 354695 Fax: (206) 685 4696 4225 Roosevelt Way NE, # 100 Seattle, WA 98105-6099 http://depts.washington.edu/ceeh/ServiceCores/FC5/FC5.html _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor