Hello Thomas,
I am sure senior members of the list will have more to say, here is my
$0.02.

logFC is the coefficient of the treatment in your model. Assuming that you
have a model with only one treatment

log Int_g = b0 + b1 * trt

b1 = logFC

The CI of logFC can be found in the same manner as you would do in normal
linear regression, but here instead of usual t(0.975, df) quantile, you
should use the moderated t quantile ie t(0.975, df.residual + df.prior)

So the 95% CI for logFC will be

logFC -+ t(0.975, fit3$df.residual + fit3$df.prior) * fit3$stdev.unscaled *
sqrt(fit3$s2.post)


Please correct me if I am wrong.


Thanks,
S.

On Thu, Oct 28, 2010 at 7:46 AM, Timothy Wu <2huggie@gmail.com> wrote:

> HI,
>
> Is there a way to report the CI of logFC from topTable in limma? I googled
> around and it doesn't seem easy to find. I was expecting the option to be
> in
> topTable().
>
> Thanks,
>
> Timothy
>
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