[BioC] Limma and time-course data

[Naomi Altman]

Usually you would fit a factorial design and compile the contrasts 
into 3 F-tests: time, strain and interaction.

--Naomi

At 12:25 PM 3/2/2006, michael watson (IAH-C) wrote:
>Thanks for your help, but one more question: if I have two factors, 
>one of which is time, and the other is strain, and say I have used a 
>common reference, there should be two F tests, one for time and one 
>for strain, no?
>
>________________________________
>
>From: Gordon Smyth [mailto:smyth at wehi.edu.au]
>Sent: Thu 02/03/2006 1:45 AM
>To: michael watson (IAH-C)
>Cc: bioconductor at stat.math.ethz.ch
>Subject: RE: [BioC] Limma and time-course data
>
>
>
>You will need at least as many contrasts as time points minus one. So
>if you have 3 times, you need at least 2 contrasts. It is just like
>oneway anova.
>
>Cheers
>Gordon
>
>At 09:39 AM 2/03/2006, michael watson \(IAH-C\) wrote:
> >Hi Gordon
> >
> >And a lightbulb goes on just above my head!  It was beginning to
> >confuse me where the F test came in.
> >
> >So once I have fit the contrasts (given that they span the entire
> >time course, so if I have endpoint-startpoint as default, I will be
> >OK) I can access the F statistic through the fitted model
> >object?  And this has a significance value associated with it?
> >
> >Thanks alot :)
> >
> >Mick
> >
> >________________________________
> >
> >From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> >Sent: Wed 01/03/2006 9:59 PM
> >To: michael watson (IAH-C)
> >Cc: bioconductor at stat.math.ethz.ch
> >Subject: [BioC] Limma and time-course data
> >
> >
> >
> >Dear Mike,
> >
> >limma does exactly what you want.  The approach outlined in the
> >User's Guide (and in the workshop)
> >  finds genes which change over time without worrying about which
> > particular time the genes differ
> >at.  I think you may have missed the fact that the approach uses the
> >F-test, not the individual
> >contrast p-values.  You will get the same F-test regardless of how
> >you specify the contrasts, as
> >long as the contrasts span all the times.
> >
> >As far as verbosity is concerned, limma is a general purpose
> >program, not specifically for time
> >courses.  So to create the F-test, you do need to explicitly setup a
> >set of contrasts.  Strictly
> >speaking, I could get limma to make a set of contrasts automatically
> >if it is known that you want
> >to do an F-test.  But making the contrasts takes only a few lines of
> >code (as you show below), so
> >I can live with that, at least for now.
> >
> >Cheers
> >Gordon
> >
> > > Date: Tue, 28 Feb 2006 12:30:47 -0000
> > > From: "michael watson \(IAH-C\)" <michael.watson at bbsrc.ac.uk>
> > > Subject: [BioC] Limma and time-course data
> > > To: <bioconductor at stat.math.ethz.ch>
> > >
> > > Hi
> > >
> > > Googling the list shows this up to be a rather hot topic, but I just
> > > wanted to ask a few more questions.
> > >
> > > Firstly, it seems the plan for tackling time course data within limma is
> > > to treat each time-point/treatment combination as a coefficient to be
> > > estimated.  Thus, to ask "which genes are changing over time", one must
> > > fit contrasts that compare every single time point to every other time
> > > point, pairwise, and look for any gene that is significant in one or
> > > more of those comparisons.  Is that correct?
> > >
> > > I am also a tad confused by the documentation, which states (on page
> > > 47):
> > >
> > > "> cont.wt <- makeContrasts(
> > > + "wt.6hr-wt.0hr",
> > > + "wt.24hr-wt.6hr",
> > > + levels=design)
> > >> fit2 <- contrasts.fit(fit, cont.wt)
> > >> fit2 <- eBayes(fit2)
> > >
> > > Any two contrasts between the three times would give the same result.
> > > The same gene list
> > > would be obtained had "wt.24hr-wt.0hr" been used in place of
> > > "wt.24hr-wt.6hr" for example."
> > >
> > > I'm confused why "wt.24hr-wt.0hr" and "wt.24hr-wt.6hr" would give the
> > > same gene list.  The first looks for differences in wt between time
> > > points 0 and 24, and the second looks for differences between time
> > > points 6 and 24.
> > >
> > > I guess, to me, this all seems a bit verbose and difficult, particularly
> > > for large time-course experiments where many biologists want to subset
> > > their data to those genes that change over time and thus want to ask the
> > > question "does time have an effect on the expression of my gene?" and
> > > are not particularly bothered, at this stage, which particular time
> > > points those genes differ at.
> > >
> > > Thanks in advance
> > >
> > > Mick
> >
> >
> >
> >
>
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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)
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