[BioC] Most stable gene pairs in array experiment

[Naomi Altman]

It sounds to me like you are looking for var(geneA-geneB).
--Naomi

At 05:54 AM 10/19/2009, anna freni sterrantino wrote:
>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 at gmail.com>
>A: bioconductor at 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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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
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