[BioC] limma analysis of 2-color experiment with tech reps [was: Help with]

[Gordon K Smyth]

Dear Guillaume,

I am going to assume that the main purpose of your experiment is to find 
genes for which the d7 vs d1 response is different between the two groups 
of patients.

> Date: Fri, 20 May 2011 15:44:45 +0200
> From: Guillaume Meurice <guillaume.meurice at igr.fr>
> To: Guillaume Meurice <guillaume.meurice at igr.fr>
> Cc: bioconductor at stat.math.ethz.ch
> Subject: Re: [BioC] Help with
>
> Sorry, I made some mistake in my previous mail, into the contrast matrix 
> (bad copy paste from another project), so here I have corrected them.
>
>> I have a question regarding the way to properly design biological 
>> replicate and technical replicates.
>>
>> In the projet, we have two groups of sample : R (respond to the 
>> treatment), NR (no response). For each groups, there is several 
>> replicates (3) that come from different patients (so not strictely 
>> biological). Each patient have two sample : one at day one(d1), the 
>> second after one week (d7) The hybridization are planned to be 
>> performed in dual color, with dye-sap.
>>
>> Here is the target file :
>>
>> Cy3	Cy5	Patient	Issu	TechnicalReplicat
>> d1	d7	A	R	1
>> d7	d1	A	R	1
>> d1	d7	B	R	2
>> d7	d1	B	R	2
>> d1	d7	C	R	3
>> d7	d1	C	R	3
>> d1	d7	D	NR	4
>> d7	d1	D	NR	4
>> d1	d7	E	NR	5
>> d7	d1	E	NR	5
>> d1	d7	F	NR	6
>> d7	d1	F	NR	6
>>
>>
>> my question is how to properly design the matrix design and the 
>> contrast matrix to answer the difference between the two groups ? Which 
>> column should I use as biological replicat (so as I can use the 
>> duplicateCorrelation function) ?
>>
>> here is how I've started, but I can't figure out how to use 
>> duplicateCorrelation with this design
>>
>> design <- cbind(
>> 		R_D7vsD1  = c(-1,1,-1,1,-1,1,  0,0, 0,0, 0,0),
>> 		NR_D7vsD1 = c( 0,0,0,0,0,0,-1,1,-1,1,-1,1)
>> )

Since you have gone to the trouble of dye-swapping, you should also 
include an intercept term in the design matrix, so as to soak up any 
probe-specific dye effects:

   design <- cbind(Dye=1,design)

Then

   cor <- duplicateCorrelation(MAn, design, weights=NULL,
          block=targets$TechnicalReplicat)

   fit <- lmFit(MAn, design, weights=NULL,
     block=targets$TechnicalReplicat, correlation=cor$consensus)

Best wishes
Gordon

>> fit <- lmFit(MAn, design, weights = NULL)
>> cont.mat = makeContrasts(NRvsR = NR_D7sD1 - R_D7vsD1, levels = design)
>> fit2 <- contrasts.fit(fit, cont.mat)
>> fit2 <- eBayes(fit2)
>>
>>
>> Many thanks by advance for any help.
>>
>> --
>> Guillaume

______________________________________________________________________
The information in this email is confidential and intend...{{dropped:4}}