[BioC] How to get and save normalized data from limma

[Mark Cowley]

Hi Jixin,
So you have 6 arrays, and thus 12 channels of data.
Do you want a heatmap of the 12 columns of red and green? If so, have  
a look at ?RG.MA in limma.
Do you want a heatmap of the 6 sets of log ratios of Red vs Green on  
each array? If so they're in MA$M

cheers,
Mark

On 11/09/2008, at 12:56 PM, Wang, Jixin wrote:

> Hi Mark,
> Thank you very much for your kind reply.
>
> I want to get normalized cy3 and cy5 channel data and tend to look  
> at the correlation (scatter plot) of normalized data between  
> biological replicates and dye swaps. But I can’t figure out R code  
> for this task. I will use MeV(TM4) and Cluster/TreeView software to  
> do the clustering.
>
> Here is my target file:
>
> SlideNumber	FileName	Cy3	Cy5	Date
> 13845971	13845971.gpr	R	wild type	8/12/2008
> 13845972	13845972.gpr	wild type	R	8/12/2008
> 13845392	13845392.gpr	R	wild type	8/12/2008
> 13845393	13845393.gpr	wild type	R	8/12/2008
> 13845400	13845400.gpr	R	wild type	8/12/2008
> 13845401	13845401.gpr	wild type	R	8/12/2008
>
>
> Regards,
>
> Jixin
>
> ----- Original Message -----
> From: "Mark Robinson" <mrobinson at wehi.EDU.AU>
> To: "Jixin Wang" <jixinwang at neo.tamu.edu>
> Cc: bioconductor at stat.math.ethz.ch
> Sent: Wednesday, September 10, 2008 5:00:23 PM GMT -06:00 US/Canada  
> Central
> Subject: Re: [BioC] How to get and save normalized data from limma
>
> Jixin.
>
> I believe you want the normalized log-ratios, which are stored in MA 
> $M.
>
> For example:
>
> library(gplots)
> heatmap.2(MA$M)
>
> ... of course, depending on the number of rows in your data, you may
> want to take a subset ...
>
> HTH,
> Mark
>
> On 11/09/2008, at 6:27 AM, Wang, Jixin wrote:
>
>> Dear All,
>>
>> I want to use the normalized signal intensities data to do
>> hierarchical clustering. But I don’t know how to save the normalized
>> data from LIMMA.
>>
>>
>> Below is the code:
>>
>> library(limma)
>> setwd("C:/Documents and Settings/JWang/Desktop/analysis with R/RAO")
>> targets <- readTargets("equi.txt")
>> targets
>> RG <- read.maimages(targets$FileName, source="genepix")
>> RG
>>
>> MA <- normalizeWithinArrays(RG)
>>
>> MA <- normalizeBetweenArrays(MA,method="scale")
>>
>> design <- c(-1,1,-1,1,-1,1)
>> fit <- lmFit(MA,design)
>>
>>
>> fit <- eBayes(fit)
>> topTable(fit,number=500,adjust="BH")
>>
>> volcanoplot(fit)
>>
>> Thanks a lot,
>>
>> Jixin
>>
>> _______________________________________________
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>
> ------------------------------
> Mark Robinson
> Epigenetics Laboratory, Garvan
> Bioinformatics Division, WEHI
> e: m.robinson at garvan.org.au
> e: mrobinson at wehi.edu.au
> p: +61 (0)3 9345 2628
> f: +61 (0)3 9347 0852
>
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-----------------------------------------------------
Mark Cowley, BSc (Bioinformatics)(Hons)

Peter Wills Bioinformatics Centre
Garvan Institute of Medical Research, Sydney, Australia