[BioC] RMA vs gcRMA on 2 groups of samples

[Naomi Altman]

Dear Bogdan,
Any normalization method that uses a set of arrays, reduces the 
variability among those arrays.

So, if you have 2 sets of arrays and normalize separately, you will 
find that the within set variability is smaller than the between set 
variability - i.e. you induce significant differential expression 
simply by the normalization.  To avoid this effect, when you are 
doing differential expression analysis (or sample clustering) you 
must either use methods that normalize each array separately (MAS) or 
normalize all together.

--Naomi

At 12:01 PM 11/2/2007, Bogdan Tanasa wrote:
>Greetings Naomi,
>
>thanks for reply. To generalize my question: when dealing with 2 sets of
>samples, let's say  X1, X2, ...., Xn  and  Y1, Y2, ..., Yn,
>I could run the normalization in 2 ways: A. only X(1,n) and only Y(1,n), or
>B. both X(1,n),Y(1,n). Are there any a priori statistical
>criteria that favors a way or the other ? If I  would take into
>consideration biological criteria (the things I am interested in), the
>results
>from A may sometimes look better than B', or vice versa. Thanks !
>
>Bogdan
>
>
>
>On 11/2/07, Naomi Altman <naomi at stat.psu.edu> wrote:
> >
> > Dear Bogdan,
> > I do not have an opinion on gcRMA versus RMA.  But if you are doing
> > differential expression analysis comparing the cell samples with the
> > organ samples, you need to normalize
> > all the samples together.
> >
> > --Naomi
> >
> > At 11:31 AM 11/1/2007, Bogdan Tanasa wrote:
> > >Hi folks,
> > >
> > >I would like to ask for your opinions on the following:
> > >
> > >I have 60 expression profiles of 60 samples (cells and organs in
> > >resting conditions).
> > >I normalized these arrays in many ways, including RMA.
> > >
> > >Considering the biological arguments (cells samples vs organs
> > >samples), I am planning to do the normalization separately, on the
> > >group of cell samples, and on the group of organ samples.
> > >
> > >My questions are:
> > >
> > >- after RMA normalization on separate groups of samples (cells vs
> > >organs), the results are different, but are these better ? GO analysis
> > >do not display major differences.
> > >
> > >- would gcRMA work better than RMA ? The majority of opinions in SoCal
> > >are pro-RMA.
> > >
> > >thanks,
> > >
> > >Bogdan
> > >
> > >_______________________________________________
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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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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