[BioC] Normalization using control spots

Gordon K Smyth smyth at wehi.EDU.AU
Thu Jul 23 01:35:52 CEST 2009


Hi Alison,

Without knowing the biological details of your experiment, I agree that 
modifyWeights or just plain lowess normalization looks appropriate.  These 
are the approaches that I generally recommend.

BTW, it would appear that your email was blocked from the Bioconductor 
mailing list because of the large attachments.

Best wishes
Gordon

On Wed, 22 Jul 2009, Alison Waller wrote:

> Thank you for the reply Gordon,
>
> Yes, I should have looked at the plots earlier.  It appears as if the second 
> set (16S) is not appropriate (due to variation in their response) and the 
> first set (Arab) is too small as you mentioned.
>
> It also appears as if the majority of the spots are not differentially 
> expressed so I can probably just use loess normalization on all of the spots.
>
> However, I don't want to totally ignore the data from the control spots, as 
> for some arrays the Arab control spots are further from M=0 than others, see 
> MA plots below.
>
> I decided to try using the modifyWeights function.
>
> The MA plots resulting from this look reasonable.  Do you think this is a 
> valid approach given the small number of control spots, and the fact that 
> they have higher intensities than the majority of the spots?
>
> w<-modifyWeights(array(1,dim(RGnm)), RGnm$genes$Status, c("All","Arab"), 
> c(1,2))
> MAnmw<-normalizeWithinArrays(RGnm,weights=w)
>
>
>



More information about the Bioconductor mailing list