[BioC] Most stable gene pairs in array experiment
David martin
vilanew at gmail.com
Tue Oct 20 10:08:36 CEST 2009
Exactly that what i want to do.
How could i do that on the whole matrix taking all pairs (or at least
one fixed gene ,e.g geneA and compute all var comparisons
var(geneA-geneB) var(geneA-geneC) var(geneA-geneC) and see which
variance is better ??
thanks
Naomi Altman wrote:
> 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
> Dept. of Statistics 814-863-7114 (fax)
> Penn State University 814-865-1348 (Statistics)
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