[BioC] reproducing dChip expression measure

Adaikalavan Ramasamy ramasamy at cancer.org.uk
Fri Apr 8 12:52:38 CEST 2005

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


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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