Christian, is that 36 samples x 11K variables?  Sounds like it.  Is this 
spectroscopic data?

In any case, the scores are in the list element $x as follows:

answer <- prcomp(your matrix)

answer$x contains the scores, so if you want to plot the 1st 2 pcs, you could do

plot(answer$x[,1], answer$x[,2])

Because the columns of answer$x contain the scores of the PCs in order.

[I see Jessica just answered...]

If you want the loading plot, it's going to be interesting with all those 
variables, but this will do it:

plot(1:11000, answer$rotation[,1], type = "l") # for the loadings of the 1st PC

Depending upon what kind of data this is, the 1:11000 could be replaced by 
something more sensible.  If it is spectroscopic data, then replace it with 
your frequency values.

By the way, plot(answer) will give you the scree plot to determine how many PCs 
are worthy.

Good luck. Bryan

***********
Bryan Hanson
Professor of Chemistry & Biochemistry
DePauw University

On May 7, 2012, at 6:22 AM, Christian Cole wrote:

> I have a decent sized matrix (36 x 11,000) that I have preformed a PCA on
> with prcomp(), but due to the large number of variables I can't plot the
> result with biplot(). How else can I plot the PCA output?
> 
> I tried posting this before, but got no responses so I'm trying again.
> Surely this is a common problem, but  I can't find a solution with google?
> 
> 
> The University of Dundee is a registered Scottish Charity, No: SC015096
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