[BioC] DESeq /edgeR design problem for a small RNASeq

Simon Anders anders at embl.de
Mon Jun 3 16:44:51 CEST 2013


Hi Eduardo

> The problem here is that there is only 5 common miRNAs between DESeq
> and edgeR.

This probably has little to do with the differences between edgeR and
DESeq and much more with the fact that you ask the two tools two
different questions.

With DESeq, you did this:
> #fit with the mouse and the drug
> experimento<-fitNbinomGLMs(cdsFull,count ~ mouseType + treatment)
> #fit with the mouse + drug + interaction from mouse:drug
> experimento_todos_factores<-fitNbinomGLMs(cdsFull,count ~ mouseType +
> treatment + mouseType:treatment)
>
> pvalsGLM<-nbinomGLMTest(experimento_todos_factores,experimento)

So, you compare a reduced model that accounts for the main effects that
treatment and mouseType have with a full model that also includes an
interaction between the two factors. So your null hypothesis is: "Both
mouseType and treatment might influence the genes' expression strengths,
but independently so, i.e. the effect of drug treatment on a gene's
expression does not depend on the mouseType (and likely, the effect of
the mouseType does not depend on whether the mouse was treated." Or, on
other words: You are looking for gene, where the strength of the effect
of the drug treatment is _different_ between the two mouse types.

With edgeR, you do:

> design<-model.matrix(~Mouse+Treatment) fit<-glmFit(y,design)
> lrt<-glmLRT(fit)

If I remember correctly, edgeR drops the _last_ factor to get a reduced
model. So you are comparing with the model "~ Mouse" and if you do the
same with DESeq, you will get similar results. This time, you simply ask
which genes' expression is affected by the treatment (whilst controlling
for mouseType), but you do not ask whether the strength of the drug's
effect depends on mouse type.

> The mutant has an insert to over express a gene of interest. and It's
> a different mouse from the wild type because the wild type with the
> insert did't born.

This is a very unfortunate experimental design. As your two mice differ 
in more than just the gene of interest, you will not be able to argue 
that the differences you find between the two mice is due to this gene 
and not one of the other genes in which they differ!

If the mutation was lethal in the strain you tried first but not in the 
second strain, why did you keep using the first strain as control rather 
than using wild-type mice of the second strain as controls?

   Simon



More information about the Bioconductor mailing list