Thank you James, that is very helpful.
In terms of why, I am not sure at the moment.

To be honest, I don't have any idea about the stats here.

Take the tilde for instance. searching online finds.
1. In asymptotic notation<http://mathworld.wolfram.com/AsymptoticNotation.html>
, [image: f∼phi] is used to mean that [image: f/phi->1].
2. In statistics <http://en.wikipedia.org/wiki/Statistics> and probability
theory <http://en.wikipedia.org/wiki/Probability_theory>, ‹~› means “is
distributed as”

How does that fit in with ~f?
0 compared factor variables?

On Fri, Jun 3, 2011 at 2:20 PM, john herbert <arraystruggles@gmail.com>wrote:

> Dear Bioconductors.
> I have a six column matrix of one colour array data (first 3 columns are
> case, second 3 are control), quantile normalized.
>
> I would like to do simple differential gene expression using limma.
>
> Is there a line or two of code that generates a simple design matrix for
> this scenario?
>
> I usually use a design matrix created from a targets file, and I never
> really understand lines like...  design <- model.matrix(~0+f) (what is
> ~0+f)?
>
>

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