[BioC] normalization and analysis of connected designs

[w.huber at dkfz-heidelberg.de]

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...