Hi,
if a don't mistake the present implementation of gcrma uses directly
the
quantile normalization.
Is there any command to switch off the quantile normalization, or how
can I modify the gcrma function to eliminate the quantile
normalization?
Since I would like to see the effect of other normalization
procedures
on gcrma, is it a risonable procedure to normalize the data first and
subsequently applying the gcrma intensity calculation, after having
modified the function in orther to remove the quantile normalization?
data<-ReadAffy()
data.invariant<-normalize(data, method="invariantset")
data.gcrma.inv<-gcrma(data) #
Raffaele
--
Prof. Raffaele A. Calogero
Genomics and Bioinformatics Unit
Dipartimento di Scienze Cliniche e Biologiche
c/o Az. Ospedaliera S. Luigi
Regione Gonzole 10, Orbassano
10043 Torino
tel. ++39 0116705410
Lab. ++39 0116705408
Fax ++39 0119038639
e-fax ++39 0112365410
Mobile ++39 3333827080
email: raffaele.calogero@unito.it
www: www.bioinformatica.unito.it
On Jun 2, 2004, at 7:09 AM, Raffaele Calogero wrote:
> Hi,
> if a don't mistake the present implementation of gcrma uses directly
> the quantile normalization.
> Is there any command to switch off the quantile normalization, or
how
> can I modify the gcrma function to eliminate the quantile
> normalization?
>
> Since I would like to see the effect of other normalization
> procedures on gcrma, is it a risonable procedure to normalize the
data
> first and subsequently applying the gcrma intensity calculation,
> after having modified the function in orther to remove the quantile
> normalization?
> data<-ReadAffy()
Perhaps I am not update (I am not yet passed to the 1.4) but it seems
to me that
you should use expresso in order to get summary values if you want to
combine
different type of algorithms.
Furthermore if I don't wrong you should apply background correction
before normalization.
data<-ReadAffy()
data.gcrma<-
bg.correct.gcrma(data,gcgroup=getGroupInfo(data),estimate="mle")
data.gcrma.invariant<-normalize(data.gcrma, method="invariantset")
summary<-
expresso(data.gcrma.invariant,bg.correct=FALSE,normalize=FALSE,pmcorre
ct
.method="pmonly",summary.method="medianpolish")
Remo
