[BioC] Difference between LIMMA and Genespring

[Edwin Groot]

Hello Ming,
Hard to say something about your data without details on your
preprocessing.

The biggest difference in my experience is from the background
subtraction and normalization steps. Check the normalization section of
Agilent Feature Extraction software. This is what gives the green and
red processed values. We use Arabidopsis 4x44k slides.

Personally, I do not use the Agilent processed values. The log-fold
changes fishtail at low expression levels.
That is why I see the differences there. I start with g(and
r)MeanSignal and g(and r)BGMedianSignal, and use limma to do the
background subtraction and normalization steps.

Edwin
-- 
On Mon, 12 Dec 2011 14:42:38 +0100
 "Jin, Ming" <ming.jin at helmholtz-muenchen.de> wrote:
> Dear Sir/Madam,
> 
> The bioinformaticist whom we cooperated with analyzed the Agilent
> microarray data with LIMMA and Genespring. As what she said, LIMMA
> should be more stringent than Genespring, so that we can get more
> genes with Genespring analysis, but in fact we get less genes by
> Genespring sometimes and sometimes ¼ of the genes are different, even
> we both use ANOVA and Benjamini & Hochberg for statistic analysis. So
> my question is:
> 1 Is this kind of situation reasonable?
> 2 What' the reason for the different results between LIMMA and
> Genespring?
> 
> Best wihses!
> 
> Ming
> 
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Dr. Edwin Groot, postdoctoral associate
AG Laux
Institut fuer Biologie III
Schaenzlestr. 1
79104 Freiburg, Deutschland
+49 761-2032948