[BioC] normalisation assumptions (violation of)

[M Perez]

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". 

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.

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

 
 --- J.delasHeras at ed.ac.uk escribió:

> Quoting Sean Davis <sdavis2 at mail.nih.gov>:
> 
> [...]
> > You can certainly try loess and see how the result
> looks, as scatterplots
> > are notorious for "hiding" where the data are most
> dense.  Alternatively,
> > you could try "rotating" the scatterplot until the
> body of the data is where
> > you think it should be--I don't know if there is a
> method in Bioconductor
> > that does this, though.
> >
> > Sean
> 
> Thanks Sean.
> 
> I already tried loess, and this is the MA plot for
> the first set of 
> data looks like this:
> 
> http://mcnach.com/MISC/MAplots2.png
> 
> which looks okay to me. You see the ascending
> diagonal is denser, which 
> contains all those newly activated spots. I knew a
> few genes that were 
> expected to be there (from RT data) and they line up
> nicely on that 
> diagonal.
> 
> This was without substracting background.
> When I attempted to correct for background I run
> into problems. Mainly 
> because some slides have a higher bkg than usual,
> and the signal is 
> lower than the local bkg for a good number of spots.
> When I use 
> "subtract" as a bkg correction method, it results in
> many negative 
> intensities, and those spots are removed. I then
> tried "half" to 
> overcome this, so that negative values are turned
> into an arbitrary 
> 0.5... and this totally flattened the MA plot, and
> nothing was 
> statistically DE. I showed this on a previous
> thread:
> 
> http://mcnach.com/MISC/MAplots1.png
> 
> It's very striking. It leaves me no other choice but
> not removing 
> background (which is increasingly looking like the
> best option in 
> general, in my still short experience...)
> 
> 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
> Swann Building, Mayfield Road
> University of Edinburgh
> Edinburgh EH9 3JR
> UK
> 
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