[BioC] normalisation assumptions (violation of)

[J.delasHeras at ed.ac.uk]

Quoting M Perez <perezperezmm at yahoo.es>:

> Hi Jose,
>
> I think you should correct for background since as you
> have commented you have slides with high background
> intensity and you want to remove background biass. I
> dont know if you have already tried "normexp".

Hi Manuel,

I haven't really. I did a long time ago and what put me off was having 
to search for the right offset, when I was hoping for something a bit 
more "automatic" (and at the time I used LimmaGUI, which is a bit more 
tedious if you want to experiment a little). I should try that.
However, I notice that the background usually appears to have little or 
nothing to do with the signals measured. The background tends to be 
very uniform across the slide, and the fact that I get "negative spots" 
where you see less signal on the actual spot than around it, makes me 
think that the cDNA spotted acts as a pretty good block against that 
general background. In other words, I am not convinced that the 
background measured on the glass has much to do with the signal I 
measured on a spot of DNA, and substracting background may be actually 
a bad thing to do.
Another reason I think background substraction doesn't matter much, is 
that on the occasions when I do see some pattern on the background 
(using 'imageplot' for instance, you can tune the ranges to display to 
enhance and view those patterns), it often doesn't translate on a 
pattern when you display the red/green ratios, or the signals on their 
own. Not always, but quite often, from what I've seen. And when you do 
get some scratches that affect clearly the signal measured, it might 
make more sense to flag those spots... or to simply rely on the fact 
that there should be enough replicates, so an odd measurement should 
not affect the outcome too much (hopefully if on another slide I have 
another scratch it will not affect the very same spots again :-)
I think I like Henrik Bengtsson's idea about measuring the background 
inherent to a particular scanner, and substract that instead... but I 
haven't yet explored that properly (hangs head in shame)... the probelm 
with being a one-man operation is that you're pressed to get results 
that are "good enough" to continue the biology, rather than spending 
too much time in working out what's teh best way to get the most of the 
data available. If only I could clone myself... but then I wouldn't 
like to work with myself... ;-)

Right now I am exploring another avenue: repeating those experiments 
that gave me high background with view to remove the offending slides 
and use something of better quality. In this case it's relatively 
simple, but many tiimes I will not have the luxury, therefore I still 
want to understand the problem with background better.


> Anycase and talking about the normalization process I
> think you dont should be so worry about the violation
> of the number of genes DE in your normalization
> process. I have been working with similar experiment
> that you mentioned using print-tip-loess and the
> results were prety good.

I'm glad to hear that. I had similar comments from other sources, and I 
must admit that the (very) few controls I had in my experiment seem to 
behave properly if apply print-tip-loess (and no bkg correction, 
because when I do I run into problems, as I mentioned in another thread)


> It is true that the normalization process is basesd in
> some assumptions. But not single microarray experimen
> fullfil these assumptions...
> HTH
> Manuel

I am aware that loess is pretty robust... I just wasn't sure that it 
was robust enough in an experiment such as this, where I expect the 
average median of ratios to be above 1 (although not by much, 
admittedly).

Thanks for all the comments. I will definitely explore the normexp bkg 
correction method.

Jose

-- 
Dr. Jose I. de las Heras                      Email: J.delasHeras at ed.ac.uk
The Wellcome Trust Centre for Cell Biology    Phone: +44 (0)131 6513374
Institute for Cell & Molecular Biology        Fax:   +44 (0)131 6507360
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