[BioC] time series data edgeR?
lianoglou.steve at gene.com
Mon Dec 16 18:12:51 CET 2013
On Mon, Dec 16, 2013 at 8:57 AM, Ryan <rct at thompsonclan.org> wrote:
> Yes, edgeR can handle this case. You have a couple of options. The
> conceptually simplest one is to treat the timepoint as a second factor and
> fit a two-factor additive model (i.e. model.matrix(~genotype + timepoint) ).
> Another option is to use natural splines. This is an approach that I am not
> personally experienced with, but it has been discussed before on this list,
> so you should be able to find an example in the archives. Personally, I
> would recommend using the two-factor analysis initially, and only switching
> to something more complex if you decide you need it.
To add to Ryan's advice -- I'm pretty sure there is an example of
using splines for timecourse data in the limma user's guide. Assuming
so, the least effort required to get a first round analysis by
following along there would be to apply limma::voom to your count
data, then follow the spline method from the user's guide accordingly.
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