  We propose a new distance metric for DNA sequences, which can be defined on
any evolutionary Markov model with infinitesimal generator matrix Q. That is
the new metric can be defined under existing models such as Jukes-Cantor model,
Kimura-2-parameter model, F84 model, GTR model etc. Since our metric does not
depend on the form of the generator matrix Q, it can be defined for very
general models including those with varying nucleotide substitution rates among
lineages. This makes our metric widely applicable. The simulation experiments
carried out shows that the new metric, when defined under classical models such
as the JC, F84 and Kimura-2-parameter models, performs better than these
existing metrics in recovering phylogenetic trees from sequence data. Our
simulation experiments also show that the new metric, under a model that allows
varying nucleotide substitution rates among lineages, performs equally well or
better than its other forms studied.
