Data from: Probabilistic distances between trees

Most existing measures of distance between phylogenetic trees are based on
the geometry or topology of the trees. Instead, we consider distance
measures which are based on the underlying probability distributions on
genetic sequence data induced by trees. Monte Carlo schemes are necessary
to calculate these distances approximately, and we describe efficient
sampling procedures. Key features of the distances are the ability to
include substitution model parameters and to handle trees with different
taxon sets in a principled way. We demonstrate some of the properties of
these new distance measures and compare them to existing distances, in
particular by applying multidimensional scaling to data sets previously
reported as containing phylogenetic islands.