[BioC] design a modelMatrix with no common references
Naomi Altman
naomi at stat.psu.edu
Mon Jul 13 20:20:39 CEST 2009
As I have noted elsewhere in the list, it is often easier to do the
analysis using Single Channel analysis, particularly if the only
blocking factor is the array.
The 2-way ANOVA is certainly more easily set up this way, although
depending on the design, a 2x2 can be done using 2-channel analysis
as long as one is very careful about setting up the
contrasts. (Sorry, I am not up for setting this up for anyone at present.)
--Naomi
At 01:31 PM 7/13/2009, Robert Castelo wrote:
>hi Giusy,
>
>so then I understand that the only way to go with two-color 2x2
>factorial design without a common reference RNA source is to treat each
>combination of factors as an independent experiment, right?
>
>(i initially understood from the last emails that there was an
>alternative by using the parameters argument to the modelMatrix()
>function, but i understand now this alternative cannot be employed)
>
>robert.
>
>On Mon, 2009-07-13 at 11:23 -0400, Giusy Della Gatta wrote:
> > Hi Robert,
> > I saw the example used in chapter 11.5. The problem is that
> > I don't have any common reference that I can use to normalize
> > the data, while in the chapter they are a comparing everything against
> > the "Pool".
> >
> >
> > G
> >
> >
> >
> >
> > -----Original Message-----
> > From: Robert Castelo [mailto:robert.castelo at upf.edu]
> > Sent: Monday, July 13, 2009 6:00 AM
> > To: James W. MacDonald
> > Cc: Giusy Della Gatta; bioconductor at stat.math.ethz.ch
> > Subject: Re: [BioC] design a modelMatrix with no common references
> >
> > James, Guisy,
> >
> > if you let me make a question about what you're discussing.
> >
> > why do you say that the two-color 2x2 factorial design without a common
> > reference RNA source is "a lot of work" ??
> >
> > (i was actually wondering how would be the 11.5 example of the Limma
> > user's guide without a common RNA source)
> >
> > thanks!
> > robert.
> >
> > On Fri, 2009-07-10 at 10:14 -0400, James W. MacDonald wrote:
> > > Hi Guisy,
> > >
> > > You really have two different experiments here, so I don't know if limma
> > > is going to want to do things automatically for you without warnings or
> > > incorrect model matrices. However, I think you want to use the
> > > parameters argument to modelMatrix() rather than the ref argument (since
> > > you have two different reference samples).
> > >
> > > > targets <- matrix(paste(rep(c("Myc","Rag"), each=4),
> > > rep(c("CD3","PBS"), each=2, times=3)[2:9], sep = "_"), byrow=T, ncol=2)
> > > > targets
> > > [,1] [,2]
> > > [1,] "Myc_CD3" "Myc_PBS"
> > > [2,] "Myc_PBS" "Myc_CD3"
> > > [3,] "Rag_CD3" "Rag_PBS"
> > > [4,] "Rag_PBS" "Rag_CD3"
> > > > colnames(targets) <- c("Cy3","Cy5")
> > > > rownames(targets) <- paste("Array", 1:4)
> > > > targets
> > > Cy3 Cy5
> > > Array 1 "Myc_CD3" "Myc_PBS"
> > > Array 2 "Myc_PBS" "Myc_CD3"
> > > Array 3 "Rag_CD3" "Rag_PBS"
> > > Array 4 "Rag_PBS" "Rag_CD3"
> > > > parameters <- cbind(First=c(-1,1,0,0), Second=c(0,0,-1,1))
> > > > rownames(parameters) <- c("Myc_PBS","Myc_CD3","Rag_PBS","Rag_CD3")
> > > > parameters
> > > First Second
> > > Myc_PBS -1 0
> > > Myc_CD3 1 0
> > > Rag_PBS 0 -1
> > > Rag_CD3 0 1
> > > > modelMatrix(targets, parameters)
> > > Found unique target names:
> > > Myc_CD3 Myc_PBS Rag_CD3 Rag_PBS
> > > First Second
> > > Array 1 -1 0
> > > Array 2 1 0
> > > Array 3 0 -1
> > > Array 4 0 1
> > > Warning message:
> > > In modelMatrix(targets, parameters) :
> > > number of parameters should be one less than number of targets
> > >
> > > But that seems like a lot of work, as the parameters matrix is exactly
> > > the model matrix you want.
> > >
> > > Best
> > >
> > > Giusy Della Gatta wrote:
> > > > Hi everybody,
> > > >
> > > > I have Agilent two colors expression arrays in which have
> been analyzed
> > > > two KO mice samples (myc-/- and Rag -/-) treated with CD3 and with PBS.
> > > > I have a total of 4 arrays composed as follows:
> > > > Sample Cy3 Cy5
> > > > 1. Myc24CD3 Myc_CD3 Myc_PBS (Swap)
> > > > 2. Myc24PBS Myc_PBS Myc_CD3
> > > > 3. Rag24CD3 Rag_CD3 Rag_PBS (Swap)
> > > > 4. Rag24PBS Rag_PBS Rag_CD3
> > > >
> > > > After the normalization I don't know
> > > > how to proceed for the construction of the model matrix.
> > > >
> > > > By using the suggestions of the "Direct Two Color Designs"
> example (chapter 7.4 LIMMA guide)
> > > > I did:
> > > >
> > > >
> > > >> targets
> > > > FileName Cy3 Cy5 Collection_time
> > > > 1 3_Myc24CD3gr_Myc24PBSre Myc_CD3 Myc_PBS 24h
> > > > 2 9_Myc24PBSgr_Myc24CD3re Myc_PBS Myc_CD3 24h
> > > > 3 5_Rag24CD3gr_Rag24PBSre Rag_CD3 Rag_PBS 24h
> > > > 4 4_Rag24PBSgr_Rag24CD3re Rag_PBS Rag_CD3 24h
> > > >
> > > >> designmyc= modelMatrix(targets, ref="Myc_PBS")
> > > > Found unique target names:
> > > > Myc_CD3 Myc_PBS Rag_CD3 Rag_PBS
> > > >
> > > >> designmyc
> > > > Myc_CD3 Rag_CD3 Rag_PBS
> > > > [1,] -1 0 0
> > > > [2,] 1 0 0
> > > > [3,] 0 -1 1
> > > > [4,] 0 1 -1
> > > >
> > > >> fit = lmFit(MA.Rq, designmyc)
> > > > Coefficients not estimable: Rag_PBS
> > > > Warning message:
> > > > Partial NA coefficients for 45018 probe(s)
> > > >
> > > >
> > > > But at this point I calculated just the ratios of Myc_CD3/Myc_PBS
> > > > and Rag_Myc/Myc_PBS (I am not really interested in this last one!).
> > > > How can I specify in the model matrix design that I need two
> different references
> > > > to calculate the following logratios: Myc_CD3/Myc_PBS,
> Rag_Myc/Rag_PBS?
> > > >
> > > >
> > > > Thank you in advance!
> > > > Giusy
> > > >
> > > >
> > > > _______________________________________________
> > > > Bioconductor mailing list
> > > > Bioconductor at stat.math.ethz.ch
> > > > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > > > Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
> > >
> >
> >
>
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Naomi S. Altman 814-865-3791 (voice)
Associate Professor
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
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