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I am using limma to analyse differential gene expressions. For modeling you need a design and contrast matrix. I just want to know whether anyone has experience with it.

Suppose that expressions are from wild type (WT) and mutants (M) and these are either stimulated (S) or unstimulated (you). For wild type I have 40 expressions values and for mutant 20.

So when I want to know which genes respond differently in mutant compared to wild type, Which formula should I use for the contrast Matrix:

Diff=(M.S-M.U)-(WT.S-M.U) or Diff=(M.S/20-M.U/20)-(WT.S/40-WT.U/40)
double-beep
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stefan
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    Your question may be more appropriate at http://biostar.stackexchange.com/ as it's not a programming question _per se_. – Roman Luštrik Apr 08 '11 at 08:19
  • Not familiar with limma, but I'm pretty sure you don't want the first version as written -- you subtract `M.U` on both sides, which I presume is a typo. In general, it would make sense to normalize, as in the second version, otherwise your WT data may swamp the M. – walkytalky Apr 08 '11 at 08:35
  • Thanks, yes it is a typo.. I will ask in the recommented platform, thx – stefan Apr 08 '11 at 08:42
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    The best place to ask this is the [Bioconductor mailing list](http://bioconductor.org/help/), after reading the excellent limma [user guide](http://bioconductor.org/packages/release/bioc/html/limma.html). – Martin Morgan Apr 08 '11 at 12:35

1 Answers1

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A contrast to determine genes that respond differently in mutant compared to wild type could be:

makeContrasts('WT - M')

where M refers to both the stimulated and unstimulated mutant cells. However, I suspect, you may want something like:

makeContrasts('WT - M.S', 'WT- M.U')

which would highlight changes in the between the WT and either mutant cell.

csgillespie
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