[BioC] reproducing dChip expression measure

[Adaikalavan Ramasamy]

It appears that the attachments did not come through, probably because
of the size. Those interested can find the plots on the following URL

   http://neelix.molbiol.ox.ac.uk:8080/ramasamy/dChip/

Thank you.

Regards, Adai



On Thu, 2005-04-07 at 16:01 +0100, Adaikalavan Ramasamy wrote:
> I am trying to reproduce the dChip expression measure from the dChip
> software with BioConductor packages. I am aware that dChip is not open
> source but I would like to get as close as I can. Thus, I compare the
> dChip expression measure from both softwares applied on a small datasets
> of 12 arrays with approximately 16000 probesets.
> 
> Going through mailing archive I found that I can use the following
> combinations of values for parameters to feed through expresso
> 
> 	 model	pmcorrect.method   bgcorrect.method 
> 	 1        "pmonly"   	     "none"
> 	 2        "subtractmm"       "none"
> 	 3 	  "pmonly"    	     "mas"
> 	 4     	  "subtractmm"       "mas"
> 
> with the following generic incantation to expresso :
> 
>   expresso( ReadAffy(), normalize.method="invariantset", 
>             bgcorrect.method=???, pmcorrect.method=???,
>             summary.method="liwong"
>           )
> 
> 
> The correlation of the values are high and similar ( around 0.90 ). I
> ahve attached both the scatterplot and hexbin of expression measures
> from these two softwares under different models with the line of
> identity in red. It suggests that :
> 
> a) Majority of the values are concentrated in the lower regions
> b) The appears to be highly correlated values at higher end but they are
> not perfectly identical
> c) the MM subtracted data gives more dis-agreement at lower range but
> much closer to line of identity at higher range
> d) mas5 background correction does not appear to make much difference
> 
> 
> Can other members of the list comment on 
> a) if they seen similar findings
> b) if these results are expected and sensibility
> c) what else can I try to increase the reproducibility 
> 
> 
> Eventually I plan on applying BioConductor's version of dChip expression
> measure to few other datasets, so it would be useful to use the most
> reproducible version from BioConductor.
> 
> Thank you very much.
> 
> Regards, Adai
> 
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