Hi  David,
not sure what do you mean with stable, 
but you might be interested in correlation, 

a=matrix(sample(1:100),4,5)
rownames(a)=paste("gene", letters[1:4])
colnames(a)=paste("cond", letters[1:5])
  >a
cond a cond b cond c cond d cond e
gene a     95     31      3      9     93
gene b     16     67     83     81     86
gene c     59     79     44     77     39
gene d     36     92     41     57     66
> cor(t(a))
          gene a     gene b     gene c     gene d
gene a  1.0000000 -0.5362894 -0.3830295 -0.1109239
gene b -0.5362894  1.0000000 -0.1710537  0.3790986
gene c -0.3830295 -0.1710537  1.0000000  0.4612277
gene d -0.1109239  0.3790986  0.4612277  1.0000000

and then  across all the pairs the most correlated will be those 
that have  a correlation value that is close to  |1|.
The correlation tells you how much close are two variables in terms
of linear relationship.

Hope this helps.
Cheers

A



Anna Freni Sterrantino
Ph.D Student 
Department of Statistics
University of Bologna, Italy
via Belle Arti 41, 40124 BO.




________________________________
Da: David martin <vilanew@gmail.com>
A: bioconductor@stat.math.ethz.ch
Inviato: Lun 19 ottobre 2009, 10:37:08
Oggetto: [BioC] Most stable gene pairs in array experiment

Hi,
I have the following matrix with normalized log2 values:
CondA    CondB    CondC    CondD    CondE
geneA    -6.19    -5.74    -5.82    -5    -5.59
geneB    -6.33    -5.32    -5.6    -4.88    -5.39
geneC    -6.15    -6.07    -5.6    -4.88    -5.9
geneD    -6.57    -6.11    -6.36    -5.36    -5.96
geneD    -6.74    -6.2    -5.49    -5.35    -5.95
geneE    -6.75    -6.24    -5.73    -5.63    -6.02


Created as follows:
geneA<-c(-6.19,   -5.74,   -5.82,   -5,  -5.59)
geneB<-c(-6.33,   -5.32,   -5.6,    -4.88,   -5.39)
geneC<-c(-6.15, -6.07, -5.6, -4.88, -5.9)
geneD<-c(-6.57,   -6.11,   -6.36,   -5.36,   -5.96)
geneD<-c(-6.74,   -6.2,    -5.49,   -5.35,   -5.95)
geneE<-c(-6.75,   -6.24,   -5.73,   -5.63,   -6.02)

mygenes<-rbind(geneA, geneB, geneC, geneD, geneE)
colnames(mygenes)<-c("CondA",   "CondB",   "CondC",   "CondD",
"CondE")

I'm looking for most stable pair genes across conditions. I'm not looking for individual gene variance but really for most stable pairs ratios.
For e.g What is the variance of geneA vs geneB across all conditions. What is the most stable pair ?

Any help would be appreciated.

david

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