[BioC] limma - paired design

Naomi Altman naomi at stat.psu.edu
Wed Oct 24 20:01:42 CEST 2007


That looks right.

The correlation that is computed is the within subject 
correlation.  In the limma "block" model, the correlation is the same 
for 0-6, 6-24 and 0-24 hours.  Although this is probably a 
simplification, when there are only 3 time points and the pairwise 
comparisons are of most interest the tests obtained from this simple 
correlation structure do not differ much (usually) from most 
complicated modeling of the correlation.

--Naomi

At 12:18 PM 10/24/2007, Mayra Eduardoff wrote:
>Dear Naomi,
>
>Thanks for your reply, can I then do it like this somehow:
>
>data is my expressionSet containing all 39 Arrays, first 0h then 6h
>then 24h always the same order of samples.
>
> > block <- rep(1:13,3)
> > design <- cbind(c(rep(1,13),rep(0,26)), 
> c(rep(0,13),rep(1,13),rep(0,13)), > c(rep(0,26),rep(1,13)))
> > rownames(design) <- c("0h","6h","24")
>
>I ram not quite sure what this line does, as I don't understand what
>the correlation parameter expects in my case, but it comes from an
>example.
>
>dupcor <- duplicateCorrelation(exprs(data),design,block=block)
>
>
> > fit <- lmFit(exprs(data),design=design, block=block, correlation= 
> dupcor$consensus)
> > cont.wt <- makeContrasts("6h-0h","24h-0h", levels=design)
> > fit2<- contrasts.fit(fit,cont.wt)
>
>
>
>kind regards,
>Mayra
>
>
>
>
>On 10/24/07, Naomi Altman <naomi at stat.psu.edu> wrote:
> > Dear Mayra,
> > The variance estimator comes from doing an ANOVA with patient as
> > block.  The t-tests you want are then done using contrasts.
> >
> > --Naomi
> >
> > At 04:24 AM 10/24/2007, Mayra Eduardoff wrote:
> > >Hi,
> > >I am having problems fitting the following model into limma, I have
> > >tried many different ways of specifying the design and contrast matrix
> > >but they all seem nonsense so I won t post them here, but maybe anyone
> > >knows how to properly fit this:
> > >
> > >I have data from 13 Patients, sampled at three different time points,
> > >0h (Control), 6h Treatment, 24h Treatment, so all in all 39 arrays and
> > >I want to do paired t tests for differential expression between 6h-0h
> > >and 24h-0h (not ! an ANOVA over both Time points). Until now we have
> > >been doing this fitting the model for the 6h and 24h separately, which
> > >works fine, but in oder to take all data into account for the mod. t
> > >tests variance estimator I guess i need to fit all data into one
> > >model.
> > >
> > >kind regards,
> > >
> > >Mayra
> > >
> > >_______________________________________________
> > >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
> >
> > 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
> >
> >

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



More information about the Bioconductor mailing list