[BioC] No replicates and differential analysis !!

[lgautier@altern.org]

> While I agree wholeheartedly with what others state on the issue of
> replication and external validation (eg PCR) you might be able to do
> slightly better with a test statistic based on a probe level analysis.
> Admittedly there is no polished function for doing this in general right
> now, but something like

Wasn't the function 'ppsetApply' in 'affy' meant to be a general function
to do whatever one likes across probe sets ?



> my.abatch <- ReadAffy()
> my.Pset <- fitPLM(my.abatch)
>
> ##now assuming you have only two samples
>
> PLM.teststatistic <- (coefs(my.Pset)[,1] -
> coefs(my.Pset)[,2])/(sqrt(se(my.Pset)[,1]^2 + se(Pset)[,2]^2)
>
>
> I have observed that you do slightly better thresholding on this than FC
> (or log FC to be more exact) on spike-in datasets.
>
> Hope that helps,
>
> Ben
>
>
>
>
>
>
> On Wed, 2006-01-25 at 14:34 +0100, Nicolas Servant 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.
>>
>> Thanks for your help,
>> Regards
>>
>> Nicolas.
>>
>
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