Thanks for your comments.
Because this is the first time I used limma package. So I am very
worry I make a mistake.
The result of analysis is not very reasonable from my analysis. There
are too many small p-value in the result. I just want to use limma to
find the different methlylation gene for two phonotypes. I am not sure
that limma is suitable for this kind of data.
Thanks.
On Tue, Jul 6, 2010 at 3:59 PM, James MacDonald <jmacdon at="" med.umich.edu=""> wrote:
>
>
>>>> Jinyan Huang <huang.tju at="" gmail.com=""> wrote:
>> But in the userguider.pdf, for the "Swirl Zebra sh" example, design
is
>> defined as: design <- c(-1,1,-1,1). I just fellow this example.
>
> My bad. I saw a cbind() where you actually had a c().
>
>
>>
>> On Tue, Jul 6, 2010 at 3:31 PM, James W. MacDonald
>> <jmacdon at="" med.umich.edu=""> wrote:
>>> Hi Jinyan Huang,
>>>
>>> On 7/6/2010 4:08 AM, Jinyan Huang wrote:
>>>>
>>>> Does anyone have the exprience to use limma for two-color array:
>>>> GoldenGate Methylation Cancer Panel I (Golden Gate Cancer Panel
>>>> Methylation Illumina)
>>>>
>>>> I used it to analysis Methylation data for finding the different
>>>> methlated genes, but the result is not good. There are too many
small
>>>> p-value the result. there are biology repeat in my data. My R
code is
>>>> like this:
>>>>
>>>> library(limma)
>>>> exp<-read.table("exp.txt",F)
>>>> sample_id<-read.table("sample_id",F)
>>>> row.names(exp)<-exp[,1]
>>>> exp<-exp[,-1]
>>>> design<-read.table("design.txt",F)
>>>> explow<-exp[,design[1,]==-1]
>>>> exphigh<-exp[,design[1,]==1]
>>>> expsort<-cbind(explow,exphigh)
>>>> idlow<-sample_id[design[1,]==-1]
>>>> idhigh<-sample_id[design[1,]==1]
>>>> idsort<-c(idlow,idhigh)
>>>> colred<-rep("red",length(exphigh[1,]))
>>>> collow<-rep("blue",length(explow[1,]))
>>>> col<-c(collow,colred)
>>>> MA<-as.matrix(expsort)
>>>> exp_norm<-normalizeBetweenArrays(MA,method="scale")
>>>> design_sort<-c(rep(-1,length(collow)),rep(1,length(colred)))
>>>
>>> Wow. That's a lot of code to end up with a two-column matrix
consisting of a
>>> column of -1s and a column of 1s. Is there some reason that
modelMatrix()
>>> doesn't do what you want?
>>>
>>> I also suspect that the design matrix you came up with isn't
correct for
>>> your experiment. I can't envision how the design matrix you have
makes any
>>> sense. But without knowing the experimental design, I can't say
for sure.
>>>
>>> I would recommend finding a local statistician who might be able
to help you
>>> with this analysis.
>>>
>>> Best,
>>>
>>> Jim
>>>
>>>
>>>> fit<- lmFit(MA,design_sort)
>>>> fit<- eBayes(fit)
>>>> mylist<-topTable(fit,number=Inf,adjust="BH")
>>>>
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>>>
>>> --
>>> James W. MacDonald, M.S.
>>> Biostatistician
>>> Douglas Lab
>>> University of Michigan
>>> Department of Human Genetics
>>> 5912 Buhl
>>> 1241 E. Catherine St.
>>> Ann Arbor MI 48109-5618
>>> 734-615-7826
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>
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