[BioC] limma: paired + multiple comparisons + technical replication?

[Gordon K Smyth]

On Thu, 3 Oct 2013, Sarah Bonnin wrote:

> Dear Gordon,
>
> Thank you for your answer.
>
> The only thing is that I also want to compare all groups (1 to 1, all 
> possibilities), and use the "makeContrasts" command - so as to automate 
> better - and I'm not sure if my way of doing it is correct!
>
> Here is my code, which actually works now, but I was wondering if it was 
> really taking into account pairs as it should.

Yes.

Gordon

> targets (a bit more informative than the previous one; TR is technical replicate)
> FileName	Groups		Pairs
> Sample1	Control		1
> Sample1_TR	Control		1
> Sample2	Control		2
> Sample3	Control		3
> Sample4	Control		4
> Sample5	Treat1		1
> Sample5_TR	Treat1		1
> Sample6	Treat1		2
> Sample7	Treat1		3
> Sample8	Treat1		4
> Sample9	Treat2		1
> Sample9_TR	Treat2		1
> Sample10	Treat2		2
> Sample11	Treat2		3
> Sample12	Treat2		4
>
> techrep <- c(1,1,2,3,4,5,5,6,7,8,9,9,10,11,12) # technical replication info
>
> design <- model.matrix(~0+targets$Groups+targets$Pairs)
>  colnames(design) <- c(unique(targets$Groups),"Pairs")
>
> corfit <- duplicateCorrelation(xx, design, ndups = 1, block = techrep)
> fit <- lmFit(xx, design, block = techrep, cor = corfit$consensus)
>
> contrast.matrix <- makeContrasts(contrasts=c("Treat1-Control", "Treat2-Control", "Treat2-Treat1"), levels=design)
>  fit <- contrasts.fit(fit, contrast.matrix)
>  fit <- eBayes(fit)
>
>
> Thank you!
>
> Sarah
>
>
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Thursday, October 03, 2013 1:04 AM
> To: Sarah Bonnin
> Cc: Bioconductor mailing list
> Subject: limma: paired + multiple comparisons + technical replication?
>
> Dear Sarah,
>
> Just put Pairs in the design matrix, for example
>
>   model.matrix(~Groups+Pairs)
>
> and use duplicateCorrelation() for the biolreps.
>
> Best wishes
> Gordon
>
>> Date: Tue, 1 Oct 2013 17:55:34 +0200
>> From: Sarah Bonnin <Sarah.Bonnin at crg.eu>
>> To: "bioconductor at r-project.org" <bioconductor at r-project.org>
>> Subject: [BioC] limma: paired + multiple comparisons + technical
>> 	replication	?
>>
>> Dear list,
>>
>> This question might be a bit redundant and I apologize for it, if it
>> is, but I can't find a clear answer to what I'm trying to do.
>>
>> I am working on a set of 12 expression one-channel arrays.
>>
>> My target file is basically as follows:
>> FileName Pairs Groups
>> Sample1        1 Group1
>> Sample2        1 Group1
>> Sample3        1 Group2
>> Sample4        1 Group2
>> Sample5        1 Group3
>> Sample6        1 Group3
>> Sample7        2 Group1
>> Sample8        2 Group2
>> Sample9        2 Group3
>> Sample10        3 Group1
>> Sample11        3 Group2
>> Sample12        3 Group3
>>
>> There are several parameters to take into account:
>>
>> - I want to produce all possible pairwise comparisons (Group3-Group2,
>> Group2-Group1, Group3-Group1): "Groups" column
>>
>> - I want my design to take into account the paired samples: "Pairs"
>> column
>>
>> - The last thing is that some samples are technical replicates
>> (Sample1 with Sample2, Sample3 with Sample4, Sample5 with Sample6) and
>> I would also like to take this into account.
>>
>> I've read the "8.7 Multi-level experiments" chapter of limma user guide, which guided me into combining paired data and multiple comparisons, in which case I would do:
>>> design <- model.matrix(~0+factor(targets$Groups))
>>> colnames(design) <- unique(targets$Groups) corfit <-
>>> duplicateCorrelation(eset,design,block=targets$Pairs)
>>> fit <-
>>> lmFit(eset,design,block=targets$Pairs,correlation=corfit$consensus)
>>
>> In theory to take into account technical replicates I would use:
>>> biolrep <- c(1,1,2,2,3,3,4,5,6,7,8,9) corfit <-
>>> duplicateCorrelation(eset, block = biolrep) fit <- lmFit(eset, block
>>> = biolrep, cor = corfit$consensus)
>>
>> But how can I combine all of this?
>>
>> Is there a way to somehow pass both paired and technical replication
>> information into the duplicateCorrelation step? Or should I modify the
>> design instead to take into account the paired design?
>>
>> It is getting quite confusing for me.
>>
>> Any help greatly appreciated!
>>
>> Thanks in advance!

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