Entering edit mode
Dear Paola,
A warning is not necessarily a problem.
The call to lmFit should be:
fit <- lmFit(esetPROC,
design,block=targets$Repl,correlation=dupcor$consensus)
Have you looked at the value of dupcor$consensus, to check that is a
reasonable value?
Best wishes
Gordon
---------------------------------------------
Professor Gordon K Smyth,
Bioinformatics Division,
Walter and Eliza Hall Institute of Medical Research,
1G Royal Parade, Parkville, Vic 3052, Australia.
Tel: (03) 9345 2326, Fax (03) 9347 0852,
smyth at wehi.edu.au
http://www.wehi.edu.au
http://www.statsci.org/smyth
On Thu, 24 May 2012, Paola Sgad? wrote:
> Dear Gordon,
> thank you for your reply.
> I immediately tried the analysis you suggested but it doesn't seem
to work:
>
>> targets$Treat <- factor(targets$Treat)
>> design <- model.matrix(~Treat,data=targets)
>> dupcor <- duplicateCorrelation(esetPROC,design,block=targets$Repl)
#esetPROC is my expression set from Agi4x44Processed
> There were 50 or more warnings (use warnings() to see the first 50)
>> warnings()
> Warning messages:
> 1: In glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit,
... :
> Too much damping - convergence tolerance not achievable
> 2: In glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit,
... :
> Too much damping - convergence tolerance not achievable
> 3: In glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit,
... :
> Too much damping - convergence tolerance not achievable
> 4: In glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit,
... :
> Too much damping - convergence tolerance not achievable
> 5: In glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit,
... :
> Too much damping - convergence tolerance not achievable
>
> The warnings are all the same. I also tried to continue...
>
>> fit <-
lmFit(design,block=targets$Repl,correlation=dupcor$consensus)
> Error in gls.series(y$exprs, design = design, ndups = ndups, spacing
= spacing, :
> Length of block does not match number of arrays
>> targets$Repl
> [1] KO1 KO2 KO3 WT1 WT2 WT3 WT4 KO4 WT4 KO4 WT4 KO4 WT4
> Levels: KO1 KO2 KO3 KO4 WT1 WT2 WT3 WT4
>
> What did I do wrong?
> Thanks guys for your help, I really appreciate it!
> Cheers
> Paola
>
> On May 10, 2012, at 04:03 AM, Gordon K Smyth wrote:
>
>> Dear Paola,
>>
>> I'm not sure why you say there's a problem. duplicateCorrelation()
has no difficulty with technical and biological replicates in the same
experiment.
>>
>> You might analysis your experiment by:
>>
>> targets$Treat <- factor(targets$Treat)
>> design <- model.matrix(~Treat,data=targets)
>> dupcor <- duplicateCorrelation(y,design,block=targets$Repl)
>> fit <-
lmFit(design,block=targets$Repl,correlation=dupcor$consensus)
>> fit <- eBayes(fit)
>> topTable(fit,coef=2)
>>
>> Best wishes
>> Gordon
>>
>>> Date: Tue, 8 May 2012 16:02:12 +0200
>>> From: Paola Sgado <sgado at="" science.unitn.it="">
>>> To: bioc-devel at r-project.org
>>> Subject: [Bioc-devel] technical and biological replicates in the
same Exprset - Agi4x44
>>>
>>> HI all,
>>
>>> I'm having some problem with microarray analysis. I am a biologist
not very good with R neither with statistics!
>>
>>> I'm using Agilent 4x44 arrays and the Agi4x44Processed package. I
have basically to compare WT vs KO data. The microarray was done first
with 3 true biological replicates and later with 4 technical
replicates with a pool of RNAs.
>>
>>> My design is the following:
>>>> targets
>>> FileName Treat GErep Subject Array Repl.
>>> 549_1_4.txt KO 2 genotype 1 KO1
>>> 550_1_4.txt KO 2 genotype 2 KO2
>>> 551_1_4.txt KO 2 genotype 3 KO3
>>> 549_1_3.txt WT 1 genotype 1 WT1
>>> 550_1_3.txt WT 1 genotype 2 WT2
>>> 551_1_3.txt WT 1 genotype 3 WT3
>>> 385_1_1.txt WT 3 genotype 4 WT4
>>> 385_1_2.txt KO 4 genotype 4 KO4
>>> 385_1_3.txt WT 3 genotype 4 WT4
>>> 385_1_4.txt KO 4 genotype 4 KO4
>>> 386_1_2.txt WT 3 genotype 5 WT4
>>> 386_1_3.txt KO 4 genotype 5 KO4
>>> 386_1_4.txt WT 3 genotype 5 WT4
>>
>>> I performed normalization and filtering with the entire set of
arrays, but when I started the statistical analysis using ebayes with
limma I realized I could not treat biological (WT1,2,3-KO1,2,3) and
technical replicates (WT4-KO4) the same way.
>>
>>> I tried to use the dupcor function, but it does not work with tech
and biol replicates in the same analysis. Is there a way to bypass the
problem?
>>
>>> Thanks for your help, I really cannot find the way out....
>>
>>> Cheers
>>> Paola
>>
>>
>>
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______________________________________________________________________
>
> --
> Paola Sgad?, PhD
> COFUND-Marie Curie Research Fellow
>
> Laboratory of Molecular Neuropathology, Centre for Integrative
Biology (CIBIO), University of Trento
> Via delle Regole 101, 38060 Mattarello, Trento (TN)
> phone (office) +39-0461-282746
> fax +39-0461-283937
> email: sgado at science.unitn.it
>
>
>
>
>
>
>
>
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