computationally singular

Hi,
I have a dataset which has around 138 variables and 30,000 cases. I am
trying to calculate a mahalanobis distance matrix for them and my
procedure is like this:

Suppose my data is stored in mymatrix

S<-cov(mymatrix) # this is fine
D<-sapply(1:nrow(mymatrix), function(i) mahalanobis(mymatrix, mymatrix[i,], S))

Error in solve.default(cov, ...) : system is computationally singular:
reciprocal condition number = 1.09501e-25

I understand the error message but I don't know how to trace down
which variables caused this so that I can "sacrifice" them if there
are not a lot. Again, not sure if it is due to some variables and not
sure if dropping variables is a good idea either.

Thanks for help,

weiwei

Weiwei Shi, Ph.D

"Did you always know?"
"No, I did not. But I believed..."
---Matrix III