I realize questions about packages should go to the package maintainer, but perhaps I have an old email address suzuki3_at_is.titech.ac.jp) -- no reply. Also I have both a general, and a specific, question. General question: i've used pvclust before to assess significance of clusters and obtained reasonable results. However, on a new data set (see below) the results seem odd. I wonder if pvclust is a generally used package to assess cluster signficance, or if another package/approach is considered standard? The "approximately unbiased" feature of pvclust compared to regular boostrapping seems attractive. Specific question: the odd result I am getting concerns a tree with a very clear division into two very distinct top level clusters. However on this data set the subclusters with confidence appear low down in the tree, and the very top most division gets zero significance. I'm suspicious of this given the rather clear top-level clade structure in this data set with lots of examples and not many NA's, i.e. pretty vanilla data. Also, in a related data set there seems to be a crash: pvclst bootstraps and scales happily for a while, then prints: Bootstrap (r = 1.29)... Done. Bootstrap (r = 1.29)... Done. Error in solve.default(crossprod(X, X/vv)) : Lapack routine dgesv: system is exactly singular In addition: Warning message: In lsfit(X, zz, 1/vv, intercept = FALSE) : 'X' matrix was collinear Thank you Alan`