One drawback to our method is the fact that for each descendent sequence we model transition and transversion rates as constant along the genome. This is a gross simplification, and something that should be dealt with in future work. As mentioned above, we would also like to superimpose protein alignment on our existent statistical alignment method, in accordance with the idea behind [6] . Another point is our fixing a partition prior to analysis. It would be even more interesting to be able to incorporate a hidden Markov model approach, in which breakpoints between regions would be chosen organically from the data. We could then truly start questioning which parts of the genome behave in different ways, as opposed to being restricted to the 'trial and error' approach that is the essence of our method now.