[BioC] Analysis HumanHT-12 Illumina

Wolfgang Huber huber at ebi.ac.uk
Sat Jul 18 22:51:22 CEST 2009


Dear Stefanie,

I cannot comment directly on that "imputing function", but it could also 
be that the method by which you decide that one method produces 167 
differentially expressed genes and the other 396 is problematic: namely 
if this is a thresholding artifact (in one case, a ~140 genes just make 
over your threshold and in the other, they don't); or if your dataset is 
in fact dominated by noise, in both cases.

Of course, it could also be that this "imputing function" introduces 
substantial distortions (I cannot judge this). You will need to look at 
your data more carefully to figure this out.

	Best wishes
	Wolfgang


Stefanie Figura wrote:
> Dear all,
> 
>  
> 
> I have some problems with the analysis of the HumanHT-12 Chip from Illumina
> and hope somebody can help me.
> 
>  
> 
> I have been analysing the data using the GenomeStudio Software until now.
> Due to the fact, that some of the bead types are underrepresented on the
> array, illumina implemented a so called “imputing function”. The Techsupport
> told me that it would not make a big difference if the imputing function is
> used or not.
> 
> While comparing the results using both methods (no imputing vs imputing), I
> found that the “imputing  function” leads to more than twice as many
> differentially expressed genes (167 vs 396). 
> 
>  
> 
> I was wondering, if there is any analog function or package implemented in R
> & Bioconductor ?
> 
>  
> 
> Any kind of advice is welcome.
> 
> Thank you very much in advance!
> 
>  
> 
> Kind regards,
> 
> Stefanie
> 
>  
> 
> ----------------------------------------------------------------------------
> ---
> 
> Dipl.Chem. Stefanie Figura
> 
> Leibniz-Institut für Arterioskleroseforschung
> 
> Department Genetische Epidemiologie vaskulärer Erkrankungen
> 
> Domagkstrasse 3
> 
> 48149 Münster
> 
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-- 

Best wishes
      Wolfgang

-------------------------------------------------------
Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber



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