[BioC] affy to normalize others single chanels...

[Marcelo Luiz de Laia]

Hello,

I create a matrix with my intensities datas and read it in R.

I have a doubt:

I transform my intensities to log2 before use normalize.quantiles or 
this is not necessary?

If the transformation is not necessary, I have another two questions:

I already use normalize.quantiles on the intensities matrix with out any 
transformation and I use limma to get differentially expressed genes.

lev <- c("ConT1","ConT2","ConT3","TraT1","TraT2","TraT3")
f <- factor(Tol.targets$Target, levels=lev)
design <- model.matrix(~0+f)
colnames(design) <- lev

Tol.matrix <- read.matrix("Tolerante_m.txt")

Tol.matrix.norm <- normalize.quantiles(Tol.matrix)

Tol.matrix.fit <- lmFit(Tol.matrix.norm,design,ndups=2,spacing=1)

cont.Tra <- 
makeContrasts("TraT2-TraT1","TraT3-TraT2","TraT3-TraT1",levels=design)

Tol.matrix.fit2 <- contrasts.fit(Tol.matrix.fit, cont.Tra)
Tol.matrix.fit3<-eBayes(Tol.matrix.fit2)
UniqueGeneNames<-read.table("UniqueGeneNames.txt",sep="\t",header = 
TRUE, colClasses = "character")
Tol.matrix.fit3$genes <- UniqueGeneNames

Tol.selected.Tra <- p.adjust(Tol.matrix.fit3$F.p.value, method="fdr") < 0.05
Tol.DE.Tra.Fpvalue <- Tol.matrix.fit3$genes[Tol.selected.Tra,]
write.table(Tol.DE.Tra.Fpvalue,"Tol.DE.Tra.Fpvalue.txt",sep="\t")

Tol.DE.TraT2TraT1 <- 
topTable(Tol.matrix.fit3,number=100,coef=1,adjust="fdr")
Tol.DE.TraT3TraT2 <- 
topTable(Tol.matrix.fit3,number=100,coef=2,adjust="fdr")
Tol.DE.TraT3TraT1 <- 
topTable(Tol.matrix.fit3,number=100,coef=3,adjust="fdr")

In the topTable result I get a bigger *M* value ten times great  that 
the original value in intensities raw matrix. This is correct or this is 
because the intensities is not log transformed before?

In the limma users guide I get the information about M-value: "The 
M-value (M) is the log2-fold change, or sometimes the log2-expression 
level, for that gene." In my situation I get the log2-expression level 
(I am not sure). Fold change is not estimable im my situation?

Thanks

Marcelo
*I do not have great knowledge of the English language. I started to 
study English, more or less, one year ago. I write my messages and use, 
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Rafael A. Irizarry escreveu:

> i used normalize.quantiles on data from a similar platform and was 
> satisfied with the results. give it try..
>
> -r
>
>
>
> On Tue, 4 Jan 2005, Marcelo Luiz de Laia wrote:
>
>> Hi Bioconductors,
>>
>> A happy new year to all!
>>
>> We have a raw data from naylon membrane (cDNA) and we would like to 
>> read and normalize it on affy package.
>>
>> Anyone do this (read and normalize) in affy package? Is it possible? 
>> Is a good idea?
>>
>> Thanks a lot
>>
>> Marcelo
>>
>> _______________________________________________
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>> Bioconductor at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>
>


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