[BioC] Limma: background correction. Use or ignore?

Naomi Altman naomi at stat.psu.edu
Tue Apr 4 16:54:09 CEST 2006

We have done up to 4 scans of the same arrays at different 
intensities with little apparent degradation of the signal.  We found 
a setting of the scanner that preserved the full optical range, and 
did not try to combine data across scanner levels, although there is 
some literature on this.


At 09:35 AM 4/4/2006, J.delasHeras at ed.ac.uk wrote:
>Quoting Naomi Altman <naomi at stat.psu.edu>:
>[Hide Quoted Text]
>I have investigated this (somewhat) experimentally.  Background
>correction increases the variability of low-expression genes and
>reduces it for high expression.  This corresponds to the RMA noise
>model since background correction would double the additive variance
>but not affect the multiplicative variance (which is the dominant
>source of variance for highly expressing genes.)
>Thank you Naomi, I think this is one of the main reasons my new arrays
>suffered more
>noticeably after bkg-substraction. They contain a large number of low
>and mid-low
>intensity spots.
>I was even considering making two subsets of my spots (higher and lower
>taking those that consistently have lower signal, and analysing them
>separately (in fact,
>scanning the slides at higher power, to obtain stronger signals from
>those). I am not
>sure if I will be able to get more consistent results that way. I can
>scan at higher
>power and get reasonable intensities from the weaker spots, whilest
>keeping a low
>background... but then I have a lot of spots that are totally saturated
>and useless...
>that's why I thought of the division of the data set and double scan.
>But I haven't tried
>it yet.
>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
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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