[BioC] No replicates and differential analysis !!

[James W. MacDonald]

Nicolas Servant wrote:
> Thanks for your answer,
> But in this case, i have to choose a fold change threshold ! And it is 
> supported that the FC tends to be greater at low expression levels.
> For instance a FC greater than 2 for expression values near 50 is 
> readily seen, but it is low probability to observe FC greater than 2 for 
> expression values near 1000
> So i would like to use a more robust approach.

With only two samples, you are stuck with fold changes. However, you 
might be able to make your results more robust by filtering out those 
genes that you think are too small. I often use kOverA() in the 
genefilter package to do this.

Best,

Jim


> 
> Regards,
> Nicolas S.
> 
> Sean Davis wrote:
> 
> 
>>On 1/25/06 8:34 AM, "Nicolas Servant" <Nicolas.Servant at curie.fr> wrote:
>>
>> 
>>
>>
>>>Hello,
>>>
>>>Does anybody know a R package or function to compare expression level
>>>(affy data) of two groups with no replicates in each group ? In fact,
>>>just compare one array to an other.
>>>The purpose is to find differentially expressed genes.
>>>We cannot used statistical test (not enougth replicates), but we can
>>>used graphical approach based on scatter plot, and outliers detection
>>>approach.
>>>   
>>>
>>
>>Simply take array A and divide it by array B.  Then rank the genes by those
>>ratios.  
>>
>>Sean
>>
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>>
>> 
>>
> 
> 
> 


-- 
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
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