[BioC] Limma and time-course data

michael watson (IAH-C) michael.watson at bbsrc.ac.uk
Wed Mar 1 23:39:51 CET 2006

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 :)


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.


> 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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