[BioC] saturated spots

[Naomi Altman]

I do not have experience with ChIP experiments.  However, in 
expression experiments, we try to set the scanner range to eliminate 
saturation and let the normalization take care of equalizing the channels.

--Naomi

At 10:08 AM 1/16/2007, J.delasHeras at ed.ac.uk wrote:
>Quoting Hans-Ulrich Klein <h.klein at uni-muenster.de>:
>
> > Dear all,
> >
> > I currently analyse some selfmade oligo chips. The green channel
> > contains the results of a ChIP-experiment. The red one contains genomic
> > DNA. I read in the data and did some quality plots using limma.
> > Unfortunatly, most arrays show strong saturation effects.
> >
> > Some plots for interested readers:
> > MA-plot: http://img402.imageshack.us/img402/6323/maplotqa1.png
> > density: http://img146.imageshack.us/img146/482/densitynotlogjo9.png
> > density log2: http://img183.imageshack.us/img183/9416/densitylogmt8.png
> >
> > It is certainly not a good idea to ignore the saturation. The saturated
> > spots are not flagged by the image analysis software. (Only non-flagged
> > spots are plotted in the images above.) My solution is to set a
> > threshold value for each array manually just before the saturation peak
> > (using the density plots) and then flag all spots with intensities
> > larger than the threshold. The flagged spots are not used for
> > normalization and further analysis.
> >
> > Are there any R-packages dealing with saturation problems? Maybe for
> > detecting the threshold automatically or for correcting saturated spots
> > with non-linear transformations. I have found none.
> >
> > How do you handle such saturation effects in your data?
> >
> > Thank you very much for any suggestions,
> > Hans-Ulrich
>
>Hi Hans,
>
>there are clearly some saturated spots, but I am not sure you need to
>worry too much. They're still a small proportion of the total. I
>suppose it is reasonable to flagged the saturated spots (which you can
>find by looking at the actual raw intensity) and not include those in
>the normalisation. However I would not necessarily remove them from
>the subsequent analysis. If a spot is saturated for one channel, but
>is weak enough in the other, it may be still interesting despite the
>fact that the ratio will be off: it'll still be "big enough". The
>ratios you obtain from your arrays will not be anywhere as accurate as
>what you'll get when you validate results by PCR. They give you an
>idea of what's going on, but if you want real quantitation you have to
>validate those spots by real time (or even semiquantitative) PCR, so I
>wouldn't worry too much about some degree of saturation. saturated
>spots are still informative (bright!), depending on what happens on
>the other channel.
>
>You can use the flags to add a note of "attention" when you deal with
>those spots, if they appear in your final list of interesting genes,
>and decide individually which ones you want to trust.
>
>Perhaps you should look also into the actual sequences that give you
>the brightest signals (saturated). Perhaps you find out that the
>reason they're so bright is they're present in multiple copies in the
>genome (even if you filter them out during design, some may creep
>in)... in which case you could just ignore them from the beginning.
>
>As for correcting the range to account for saturated spots... I think
>the aroma package allows you to deal with multiple scans of the same
>slide, using different PMT settings, to re-arrange the dynamic range.
>This seems especially useful when you have some very bright spots you
>don't want to lose, but which will saturate if you scane to get decent
>intensities on the much weaker bulk. I haven't tried it myself. I
>tried another approach (MASLINER) and it did seem to work, but in teh
>end I decided it wasn't worth the effort in my particular case.
>
>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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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
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