A Probabilistic Treatment of Phylogeny and Sequence Alignment

Abstract.

Carrying out simultaneous tree-building and alignment of sequence data is a difficult computational task, and the methods currently available are either limited to a few sequences or restricted to highly simplified models of alignment and phylogeny. A method is given here for overcoming these limitations by Bayesian sampling of trees and alignments simultaneously. The method uses a standard substitution matrix model for residues together with a hidden Markov model structure that allows affine gap penalties. It escapes the heavy computational burdens of other models by using an approximation called the ``*'' rule, which replaces missing data by a sum over all possible values of variables. The behavior of the model is demonstrated on test sets of globins.