Feature selection using clustering

I have to select features using clastering method - Ward's algorithm.

Short description of dataset: 16000 records, 5400 features (float) each record. I make some subset because working on the full set causes out of memory.

Reading Matlab docs it is quite easy:

X = load('subset.data');
Y = pdist(X);
Z = linkage(Y,'ward');
T = cluster(Z,'maxclust',2); % I set 2 clasters because in my dataset is 2 classes of objects. But now, I'm not sure if it is ok.

% PCA visualization
[W, pc] = princomp(X);
scatter(pc(:,1),pc(:,2),10,T,'filled')

And now, I don't know what to do next. How can I select features? Now, I think that instead of Y = pdist(X) it should be Y = pdist(X'), because I want to have clusters of features and than select some of them, right? But the problem is Y = pdist(X') causes out of memory. I would be greatful for answer, if my way of thinking is correct.

Thank you in advance!