Re: [BioC] F-tests for factorial effects - limma

[Ramon Diaz-Uriarte]

Dear Naomi and Gordon,

Just in case it helps someone else, I am attaching a more verbose version of 
the code snippet that Gordon sent, because I found the "diag(p)
[,attr(X,"assign")==3]" non-intuitive, so I called makeContrasts explicitly.


This is the example:
*****************************************************************
## treat is a factor with three levels; age is a continuous variable.

X <- model.matrix( ~ treat*age.centered)
fit <- lmFit(d.clean, X)
p <- ncol(X)
cont.ia <- diag(p)[,attr(d.trt.BY.age3,"assign")==3]
fit.ia <- eBayes(contrasts.fit(fit, cont.ia))


############# Using my more verbose apporach

X2 <- model.matrix( ~ treat*age.centered)
colnames(X2) <- c("Intercept", "Colon", "Mama",
                             "age", "Colon.by.age", "Mama.by.age")
contrasts.trt.BY.age <- makeContrasts(Colon.by.age,
                                      Mama.by.age,
                                      levels = X2)
fit2 <- lmFit(d.clean, X2)
fit.ia2 <- eBayes(contrasts.fit(fit2,
                                contrasts.trt.BY.age))

### We can of course do instead (which I like better)
X2 <- model.matrix(~ -1 + treat + age.centered +
                              treat*age.centered)
colnames(X2) <- c("Colon", "Mama", "Normal",
                  "age", "Colon.by.age", "Mama.by.age")
contrasts.trt.BY.age <- makeContrasts(Colon.by.age,
                                      Mama.by.age,
                                      levels = X2)

*************************************************

Best,


R.






On Wednesday 22 December 2004 14:23, Gordon K Smyth wrote:
> > Date: Tue, 21 Dec 2004 17:21:19 -0500
> > From: Naomi Altman <naomi at stat.psu.edu>
> > Subject: [BioC] F-tests for factorial effects - limma
> > To: bioconductor at stat.math.ethz.ch
> >
> > I am analyzing a 2-factor factorial Affy experiment, with 3 d.f. for each
> > factor.
> >
> > I would like to get the F-tests for the main effects and interactions
> > using limma.
> >
> > I have computed all the contrasts, and got the t-tests (both unadjusted
> > and eBayes).  I do know how to combine these into F-tests "by hand" but I
> > could not figure out if there was a simple way to do this using limma.
>
> limma doesn't have any easy way to deal with main effects and interactions,
> at least not with main effects, interactions are actually simpler.  I
> haven't implemented this because I've never been able to figure out what
> one would do with these things in a microarray context.
>
> To compute F-tests for main effects and interaction, the easiest way would
> probably be to compute the SS for main effects and interactions by
> non-limma means, then use shrinkVar() to adjust the residual mean squares,
> i.e., the F-statistic denominators.
>
> If you only want F-tests for interactions, the following code would work:
>
> X <- model.matrix(~a*b)
> fit <- lmFit(eset, X)
> p <- ncol(X)
> cont.ia <- diag(p)[,attr(X,"assign")==3]
> fit.ia <- eBayes(contrasts.fit(fit, cont.ia))
>
> Now fit.ia contains the F-statistic and p-values for the interaction in
> fit.ia$F and fit.ia$F.p.value.
>
> > I had a look at FStat (classifyTestsF).  There seems to be a problem, in
> > that the matrix tstat is not premultiplied by the contrast matrix when
> > the F-statistics are computed.  So, if the contrasts are not full-rank,
> > an error is generated (instead of the F-statistics) because nrow(Q) !=
> > ncol(tstat)..  (See the lines below).
>
> No, the code is correct.  FStat is quite happy with non full rank contrasts
> but the contrast matrix must be applied using contrasts.fit() before
> entering FStat().  You should not expect to see a contrast matrix inside
> the classifyTestsF() code.
>
> Gordon
>
> > if (fstat.only) {
> >          fstat <- drop((tstat%*% Q)^2 %*% array(1, c(r, 1)))
> >          attr(fstat, "df1") <- r
> >          attr(fstat, "df2") <- df
> >          return(fstat)
> >      }
> >
> > I figured that before I fiddled with the code, I would check to make sure
> > that I didn't miss an existing routine to do this.
> >
> > Thanks in advance.
> >
> > Naomi S. Altman                                814-865-3791 (voice)
> > Associate Professor
> > Bioinformatics Consulting Center
> > Dept. of Statistics                              814-863-7114 (fax)
> > Penn State University                         814-865-1348 (Statistics)
> > University Park, PA 16802-2111
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor

-- 
Ramón Díaz-Uriarte
Bioinformatics Unit
Centro Nacional de Investigaciones Oncológicas (CNIO)
(Spanish National Cancer Center)
Melchor Fernández Almagro, 3
28029 Madrid (Spain)
Fax: +-34-91-224-6972
Phone: +-34-91-224-6900

http://ligarto.org/rdiaz
PGP KeyID: 0xE89B3462
(http://ligarto.org/rdiaz/0xE89B3462.asc)


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