[BioC] normalization and analysis of connected designs

[Ramon Diaz-Uriarte]

Dear Wolfgang,

Thanks a lot for your answer. I have to confess I am still confussed.

I understand the points you rise about the sources of variation. But I think 
there is a fundamental issue we have not addressed: the values we get for G 
and R are comming from a competitive hybridization experiment, and thus the 
value of h_3G is meaningful only when we relate it to whatever was in h_3R, 
and thus I don't think it is some absolute measure.

__If__ the competitive hybridization nature of the experiment is as relevant 
as I believe it is, then I think we __must__ go through the chain of 
connected experiments to get an estimate, regardless of the relative 
magnitude of the sources of variation.

I need to go back, re-read a few papers, check the reference that Gordon has 
suggested, and think about your message carefully, but this is the way I see 
the issue for now.


Best, and thanks again for the comments and great discussion,

Ramón


On Wednesday 02 July 2003 19:27, w.huber at dkfz-heidelberg.de wrote:
> Hi Ramon,
>
> What makes the difference between D and A hybridized on the same array,
> and on different arrays? It is (a) the between-array variation (e.g.
> because each time the spotter puts down a drop of DNA it is a a little bit
> different, or because the arrays had different surface treatments, etc.),
> and (b) the between-hybridization variation (e.g. different temperatures,
> different volumes of the reaction chamber). These two sources of variation
> need to be compared to others sources, e.g. (c) between-RNA-extraction,
> (d) between-reverse-transcription, (e) between-labeling, (f) between-dyes.
> (c)-(f) are present no matter whether you D and A are on one array or on
> different ones.
>
> That it is possible to make (a) and (b) small is shown by the fact that
> useful results have been obtained through single-color arrays such as Affy
> or Nylon membranes. Whether in your experiment (a) and (b) are small
> compared to (c)-(f) depends on your particular experiment. If they are,
> you are better of with h_3G - h_1R than with the full chain of summands. I
> have seen examples where this seemed to be the case.
>
> Anyone else?
>
> Best regards
>   Wolfgang
>
>
> On Wed, 2 Jul 2003, Ramon Diaz-Uriarte wrote:
> ... [SNIP]
>
> > I am not sure I follow this. I understand that, __if__ D and A had been
> > hybridized in the same array, then the variance of their comparison would
> > be a third of the variance of the comparison having to use the (two-step)
> > connectiion between A and D. But I am not sure I see how we can directly
> > do h_3G - h_1R
> > (if this were possible, then, there would be no need to use connected
> > designs.)
> >
> > ... [SNIP] ...
> >
> > So either way, I don't get to see how we can directly do
> > h_3G - h_1R
> >
> > But then, maybe I am missing something obvious again...

-- 
Ramón Díaz-Uriarte
Bioinformatics Unit
Centro Nacional de Investigaciones Oncológicas (CNIO)
(Spanish National Cancer Center)
Melchor Fernández Almagro, 3
28029 Madrid (Spain)
Fax: +-34-91-224-6972
Phone: +-34-91-224-6900

http://bioinfo.cnio.es/~rdiaz