[BioC] Most stable gene pairs in array experiment

David martin vilanew at gmail.com
Fri Oct 23 10:24:37 CEST 2009


Hi thanks for the answers and interesting dicussions:
Yes, indeed it's the only way i have to look for internal controls. 
Since i can't find any stable gene across conditions i assume that pairs 
can be stable (although each single gene can vary across conditions). I 
expect (geneA-geneB) to be stable (at least is what i will try).
I'm not comouting correlations since i'm not looking at all that genes 
correlate (for e.g geneA could be up regulated and gene B 
down-regulated), but geneA-geneB might remain stable !!!

thanks again,
david

Naomi Altman wrote:
> You would conclude that the pairs of genes with very low variance track 
> each other closely in the samples.
> Since the analysis is on the log-scale, this means that the fold ratio 
> is stable.  It does not mean that the two genes do not vary.  For that, 
> you would want to compute the gene-wise variance.
> 
> Naomi
> 
> At 08:30 AM 10/20/2009, Marcelo Laia wrote:
>> 2009/10/20 Michael Dondrup 
>> <Michael.Dondrup at bccs.uib.no>:
>> > Hi,
>> >
>> > you can  try something like this or use two for loops:
>> >
>> >
>> >> apply (mygenes, 1 , function(row) { apply (mygenes, 1, function(x) {
>> >> var(row-x)  } ) } )
>> >
>> >        geneA   geneB   geneC   geneD   geneE
>> > geneA 0.00000 0.04108 0.06397 0.12217 0.08233
>> > geneB 0.04108 0.00000 0.15543 0.12807 0.09365
>> > geneC 0.06397 0.15543 0.00000 0.08628 0.08903


>> > geneD 0.12217 0.12807 0.08628 0.00000 0.01517
>> > geneE 0.08233 0.09365 0.08903 0.01517 0.00000
>> >
>> >
>> > Cheers
>> > Michael
>>
>> Hi,
>>
>> I am following the discussion and I'm finding very interesting. 
>> Congratulations!
>>
>> After this, I could compare the two genes, two-by-two, and I could
>> conclude that the pair with minor variance are the two most stable
>> genes of all?
>>
>> Is this genes appropriated for qPCR internal control? Or am I totally
>> wrong here?
>>
>> Thank you very much!
>>
>> -- 
>> Marcelo Luiz de Laia
>> Universidade do Estado de Santa Catarina
>> UDESC - www.cav.udesc.br
>> Lages - SC - Brazil
>> Linux user number 487797
>>
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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)
> University Park, PA 16802-2111
> 
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