[BioC] Use of duplicateCorrelation

[Erika Melissari]

Dear Gordon,

I fixed the problem with eBayes....I used ebayes() and not eBayes() and, as 
reported in LIMMA help, "ebayes is the earlier and leaner function. eBayes 
is intended to have a more object-orientated flavor as it produces objects 
containing all the necessary components for downstream analysis. "
Then, I fixed the problem by using eBayes()

However, I did not manage to fix the problem of duplicateCorrelation()

When I define the design including the dye effect and I use this design in 
duplicateCorrelation(), the calculated consensus correlation is NaN, where 
without including the dye effect is

-0.55 (I have a dye swap design).

I have tryed to "unswap" the design also (as you suggested in a previous 
message), but I have obtained the same result, that is NaN.

I have used a different dataset with the same experimental design also and 
the result was the same: NaN

I have tryed to use the simple dye swap design for duplicateCorrelation 
computation

>design<-c(-1,1-1,1)

>biolrep<-c(1,1,2,2)
>corfit<-duplicateCorrelation(MA,design,ndups=1,block=biolrep)

then I have defined a new design

>design<-cbind(Dye=1,design)

and I have used this together with the correlation previously calculated by 
duplicateCorrelation (-0.55) for model computing

>fit<-lmFit(MA,design, block=biolrep,cor=corfit$consensus,weights=NULL)

Is this a right way of mouving aroud the problem?

Any suggestion will be appreciated.



Erika









----- Original Message ----- 
From: "Gordon K Smyth" <smyth at wehi.EDU.AU>
To: "Erika Melissari" <erika.melissari at bioclinica.unipi.it>
Cc: "Bioconductor mailing list" <bioconductor at stat.math.ethz.ch>
Sent: Saturday, January 24, 2009 03:40 AM
Subject: [BioC] Use of duplicateCorrelation


> Dear Erika,
>
> The output from fit() and eBayes() cannot be as you've given below,
> because eBayes() does not remove the $coefficient component of the fitted
> model object.  Can you please rerun your code from scratch in a new R
> session, re-reading the data and so on.
>
> Best wishes
> Gordon
>
>> Date: Thu, 22 Jan 2009 15:51:43 +0100
>> From: "Erika Melissari" <erika.melissari at bioclinica.unipi.it>
>> Subject: [BioC] Use of duplicateCorrelation
>> To: <bioconductor at stat.math.ethz.ch>
>> Message-ID: <00c001c97ca0$f1a27fe0$ba517283 at maanalysis>
>> Content-Type: text/plain
>>
>> Hello all,
>>
>> I'm studing how to use duplicateCorrelation() of LIMMA package in order 
>> to evaluate the between-arrays correlation.
>> I have a simple experiment of direct comparison with dye-swap as follows:
>> targets
>>  SlideNumber       FileName     Cy3     Cy5          Date
>> 1                             Ag_1.gpr      wt1        1RP 
>> 20/9/2008
>> 2                             Ag_2.gpr     1RP      wt1 
>> 20/9/2008
>> 3                             Ag_3.gpr      wt2         2RP 
>> 8/11/2008
>> 4                             Ag_4.gpr     2RP      wt2 
>> 8/11/2008
>>
>> I use duplicateCorrelation() as follows:
>>
>> design <- c(1,-1,1,-1)
>>> biolrep<-c(1,1,2,2)
>>> corfit<-duplicateCorrelation(MA,design,ndups=1,block=biolrep)
>>> corfit$consensus
>> [1] -0.5543286
>>
>> The correlation is negative because of dye-swap.
>> Then, I evaluate linear model as explained in limma userguide:
>>
>>> fit<-lmFit(MA,design, block=biolrep,cor=corfit$consensus,weights=NULL)
>>> summary(fit)
>>                 Length Class      Mode
>> coefficients     10807  -none-     numeric
>> stdev.unscaled   10807  -none-     numeric
>> sigma            10807  -none-     numeric
>> df.residual      10807  -none-     numeric
>> ndups                1  -none-     numeric
>> spacing              1  -none-     numeric
>> block                4  -none-     numeric
>> correlation          1  -none-     numeric
>> cov.coefficients     1  -none-     numeric
>> pivot                1  -none-     numeric
>> genes                5  data.frame list
>> Amean            10807  -none-     numeric
>> method               1  -none-     character
>> design               4  -none-     numeric
>> fit2<-ebayes(fit)
>> summary(fit2)
>>          Length Class  Mode
>> df.prior      1  -none- numeric
>> s2.prior      1  -none- numeric
>> s2.post   10807  -none- numeric
>> t         10807  -none- numeric
>> p.value   10807  -none- numeric
>> var.prior     1  -none- numeric
>> lods      10807  -none- numeric
>>> toptable(fit2,adjust="fdr")
>> Error in dim(data) <- dim : attempt to set an attribute on NULL
>>
>>
>>
>> What does it means this error message and, above all, where is the 
>> mistake in my analysis procedure?
>> I do not understand why in fit2 there are not any coefficients!
>> I would like to evaluate the dye effect also. How can I do this?
>> I tryed the inclusion of a dye effect coefficient in the design,
>>
>> design<-cbind(Dye=1,design)
>>
>> but when I calculate duplicateCorrelation corfit$consensus is NaN. Is it 
>> correct?
>>
>> Thanks very much for any kind of help in advance!
>> Best regards
>> Erika


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