[BioC] gcrma.1.0.0 vs gcrma.1.0.6 vs justGCRMA.1.0.6

James MacDonald jmacdon at med.umich.edu
Sat Apr 10 00:26:44 CEST 2004


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 at 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 at stat.math.ethz.ch
https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor



More information about the Bioconductor mailing list