Hi Simon,
I hope not to deal with these kind of experiments anymore ;)

I'm glad to know that I'm doing it correctly.

About ANOVA, I did some experiments with the edgeR anova-like test using the glmLRT function and the coef parameter. 

But as usual, both results were quite different.

About the next step, the time course analysis, can this be done with DESeq, using the time as a new covariate (as with the drug) ?

Thanks again !

On 4 Jun 2013, at 11:52, "Simon Anders" <anders@embl.de> wrote:

> Hi Eduardo
> 
> Thanks for the exaplanation. I now see what yiu are heading at.
> 
> On 04/06/13 11:01, Eduardo Andrés León wrote:
>>   (MTsD - MTcD) - (WTsD -WTcD) = Real effect of the overexpression.
> 
> Yes, this is precisely what is called an "interaction effect" and described in R's formula notation with ":" operator.
> 
> So, you use, as full model:
> 
> full_model <- fitNbinomGLMs( cds, count ~ mutation + drug + mutation:drug)
> 
> and as reduced model
> 
> reduced_model <- fitNbinomGLMs( cds, count ~ mutation + drug )
> 
> and then compare the two:
> 
> pvals <- nbinomGLMTest( full_model, reduced_model )
> 
> (As an alternative for the notation "~ A + B + A:B", you will often see the equivalent abbreviated notation "~ A * B".)
> 
> If you deal with such questions more often, it may be helpful to read a textbook on linear models and Anova. This is all quite standard stuff.
> 
>  Simon

===================================================
Eduardo Andrés León
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e-mail: eandres@cnio.es        Fax: (+34) 91 224 69 76
Unidad de Bioinformática       Bioinformatics Unit
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