Jaccard dissimilarity matrix for PCA

This sounds like something I could use..
I'm kind of new with R, meaning I've having some minor troubles all the
time...
Say I have a range of binary(0,1) variables X1 to Xn, with missing data for
different cases.
At the moment my data is a binary indicator matrix; rows representing the i
individuals or subjects, columns representing presence(1)/absence(0) of
various characteristics. 
Actually I have 5 groups of variables (102 variables in total), describing
different aspects of the subject(s) I'm studying (people; i.e. refugees).
O -> O1 to O43 
A -> A1 to A38
R -> R1 to R6
AP -> AP1 to AP8
PT -> PT1 to PT7

Can someone help me with the programming of a jaccard matrix in prabclus (or
in any other package). I'm having troubles defining the input-object to the
function, I think?
I get error messages like:
'x' must be an array of at least two dimensions
ERROR:  argument is not a matrix

Jacob

jaccard in package prabclus computes a Jaccard matrix for you.

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