[BioC] Normalizing after MAS 5.0
naomi at stat.psu.edu
Thu Jan 22 05:38:08 CET 2009
One thing to consider when doing clever things with expresso is
validating your approach.
I have found that using the same data, different normalizations can
come up with completely different lists of significantly differentially
expressing genes. If you want to share your results with others (for
example by publishing) then you need to justify your normalization
method by e.g. running experiments with known outcomes such as
spike-in genes, or extensive follow-up on another platform such as
RT-PCR. The pre-packaged methods have their problems, but at least
these problems are well-understood.
At 05:25 PM 1/21/2009, Michal Blazejczyk wrote:
>What I was wandering about more specifically was: if I run expresso
>with a different summary.method parameter (say, medianpolish for RMA),
>but select mas as the PM correction method or the background correction
>method, should I be worrying about the additional normalization as well?
>Or is it only applicable if I use summary.method=mas regardless of my
>pmcorrect.method and bgcorrect.method?
>FlexArray Lead Developer
>McGill University and Genome Quebec Innovation Centre
>James W. MacDonald <jmacdon at med.umich.edu> wrote:
> > Hi Michal,
> > Technically, the mas5 method is implemented by the function mas5(),
> > so you would certainly need to normalize after that step. Note that
> > mas5() is just a wrapper to expresso:
> > res <- expresso(object, bgcorrect.method = "mas", pmcorrect.method =
> > "mas", normalize = FALSE, summary.method = "mas", ...)
> > As for expresso(), this is a bit of a 'roll your own' function, so
> > it is incumbent upon the user to figure out whether or not the data
> > need to be normalized, which would be dependent on the arguments
> > 'normalize' and 'normalize.method'.
> > Best,
> > Jim
> > Michal Blazejczyk wrote:
> >> Hello group,
> >> According to the Bioconductor Help for function expresso():
> >> "For the mas 5.0 and 4.0 methods ones need to normalize after
> >> obtaining expression. The function affy.scalevalue.exprSet
> >> does this."
> >> What does it really mean, "for the mas 5.0 method" in this case?
> >> When calling expresso, "mas" can be set as a method for background
> >> correction, PM correction, and probe summarization. In which of
> >> these cases should the custom normalization (affy.scalevalue.exprSet)
> >> be used?
> >> Best regards,
> >> Michal Blazejczyk
> >> FlexArray Lead Developer
> >> McGill University and Genome Quebec Innovation Centre
> >> http://genomequebec.mcgill.ca/FlexArray
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