[BioC] Random Matrices

[Sean Davis]

On Thu, Apr 3, 2008 at 3:41 PM, Matthew R. Helmus <mrhelmus at wisc.edu> wrote:
> Hi Sean,
>  Thanks for your reply. I have a large data matrix (500x50) of values and I
> need to:
>  1) randomize
>  2) for each row apply a function
>  3) calculate the mean of the outputs of the function across the rows
>  4) store this mean
>  5) then repeat the loop 10,000 times to produce a vector of 10,000 random
> means.
>
>  I have used the following code, apply(X, 1, sample), to make a randomized
> matrix maintaining row sums, but the for loop runs a bit slow that creates
> each random matrix. I have not developed or found code that maintains both
> row and sum totals while randomizing.

> a <- matrix(rnorm(500*50),nc=50,nr=500)
> for(i in 1:100) {b <- apply(a,1,sample)}
> system.time(for(i in 1:100) {b <- apply(a,1,sample)})
   user  system elapsed
  1.164   0.008   1.170
> system.time(for(i in 1:100) {b <- a[,sample(ncol(a),replace=FALSE)]})
   user  system elapsed
  0.024   0.000   0.022

So, at least the randomization code can be quite a bit more efficient
than your "apply(X,1,sample)". For 10000 replicates, it runs is just
over 2 seconds.  Give this a try and then you may want to let us know
more details if you are still having problems.

Sean