[BioC] normalisation assumptions (violation of)

[J.delasHeras at ed.ac.uk]

Quoting Henrik Bengtsson <hb at maths.lth.se>:

> You haven't told us your platform.  What type of scanner do you use?

GenePix 4200AL.

>> overcome this, so that negative values are turned into an arbitrary
>> 0.5... and this totally flattened the MA plot, and nothing was
>
> Yes, 0.5 is very arbitrary.  Why not 5, 0.05, or 0.0000000000005?
> You might want to look into Kooperberg's background correction
> methods, or the ones in limma.

actually, I tried other numbers too, just to check that they did not 
have a drastic effect on the final results. I just wanted a positive 
number (actually >1 better, so that I can take logs directly) that is 
low enough so that I get a high M value when I divide the signal of teh 
other channel by it. M values of genes that have no detectable signal 
on one channel are meaningless, in that they don't represent any kind 
of fold enrichment... but they're useful to help me pick those genes.


> You haven't told us your platform.  What scanner do you have?  You
> might have an offset in your scanner (quite commonly added to avoid
> that analogue negative signals are truncated to zero), e.g. Axon and
> Agilent introduce about 20-25 units (which is significant).  With a
> simple scan protocol it is easy to check if your scanner introduce
> offset.  The method is described in
>
> H. Bengtsson, G. Jönsson and J. Vallon-Christersson, Calibration and
> assessment of channel-specific biases in microarray data with extended
> dynamical range, BMC Bioinformatics, 2004, 5:177.
>
> and the estimatation and calibration methods are in aroma.light.  The
> scanner offset is a global constant which means that you only fit a
> single parameter per channel.  That is, subtracting this "background"
> from the foreground signals does not introduce as much noise as if you
> would subtract the image-analysis estimated backgrounds unique to each
> spot.  This will leave you with less (probably no) non-positive
> signals.  It might also be enough to remove the curvature seen in your
> raw MA plots.  If so, your remaining problem will be how to estimate
> the overall relative scale factor between the two channels, which is
> only one parameter; it should be easier than using non-parametric
> curve-fit methods.

I would like to try your package aroma. I've been meaning to for a 
while. I like your reasoning. But unfortunately my "exploring" time is 
limited. You probably think that it will be a good investment of time 
to dedicate some time now to explore these issues more in depth... and 
I would agree... but unfortunately I am not able. It's not entirely my 
call...

The problem I had with negative signals is enhanced in this particular 
experiment because I happened to have a few slides with abnormally high 
background, mainly on the Cy3 channel. The high background was due to a 
problem in the preparation of teh samples. Usually I get pretty clean 
slides. I'm working on repeating the "bad" slides to help solve this.

> When you understand the bits and pieces of what's going on there you
> will also be much more careful when you pick your normalization
> method.  If would say that curve-fit (loess, lowess, spline, ...)
> normalization is often overkill and corrects for a symptome rather
> than fixing the underlying problem.  Quantile normalization can be
> interpreted as a non-parametric method that corrects for affine
> transformations, but it has a problem at the lower and higher
> intensities.  Variance stabilization methods (Rocke & Durbin, W Huber)
> have an explicit affine component in there models so they are much
> more suited to this type of transform. Plain affine normalization
> (aroma.light) corrects for affine transformation without controlling
> for variance (on purpose).  The estimatation methods also differ
> between the latter two approaches.
>
> I hope this is a good start.

As ever, your replies are very useful. I just wished I had a little 
help so that I could spend more time looking at these details in a lot 
more depth. But I will do what I can, and the replies received so far 
are all very useful for me.

Thanks!

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