[BioC] spline example from limma user's guide

[Gordon K Smyth]

Dear Juliet,

Yes, using duplicateCorrelation to estimate the within-subject correlation 
is a valid way to go.

The alternative is to set subject as an explanatory factor as Paul 
Geeleher suggested in his reply.

The first approach is statistically more powerful, the second makes fewer 
assumptions.  If you have lots of subjects, first approach might be good. 
If you have only two subjects or some subjects are distinctly different 
from others (outliers), use the second approach.

Best wishes
Gordon

> Date: Tue, 16 Apr 2013 15:10:04 -0400
> From: Juliet Hannah <juliet.hannah at gmail.com>
> To: Bioconductor mailing list <bioconductor at r-project.org>
> Subject: [BioC] spline example from limma user's guide
>
> All,
>
> In section 8.6.2 of the limma user's guide, an example is given using
> splines for time-course data. It looks like in this example, the data
> points are independent, meaning different subjects are observed at
> different timepoints.
>
> If the same subject is observed over time, is it correct to use
> duplicateCorrelation function along with the spline model. Is this the
> correct way to handle profiles of individuals in limma?
>
> What other Bioconductor approaches have people used? I can't tell if EDGE
> (Leek and colleagues) is updated/maintained.
>
> Thanks,
>
> Juliet
>

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