Indexed on: 23 Nov '15Published on: 23 Nov '15Published in: Computer Science - Data Structures and Algorithms
The subtree prune-and-regraft (SPR) distance metric is a fundamental way of comparing evolutionary trees. It has wide-ranging applications, such as to study lateral genetic transfer, viral recombination, and Markov chain Monte Carlo phylogenetic inference. Although the rooted version of SPR distance can be computed relatively efficiently between rooted trees using fixed-parameter-tractable maximum agreement forest (MAF) algorithms, no MAF formulation is known for the unrooted case. Correspondingly, previous algorithms are unable to compute unrooted SPR distances larger than 7. In this paper, we substantially advance understanding of and computational algorithms for the unrooted SPR distance. First we identify four properties of minimal SPR paths, each of which suggests that no MAF formulation exists in the unrooted case. We then prove the 2008 conjecture of Hickey et al. that chain reduction preserves the unrooted SPR distance. This reduces the problem to a linear size problem kernel, substantially improving on the previous best quadratic size kernel. Then we introduce a new lower bound on the unrooted SPR distance called the replug distance that is amenable to MAF methods, and give an efficient fixed-parameter algorithm for calculating it. Finally, we develop a "progressive A*" search algorithm using multiple heuristics, including the TBR and replug distances, to exactly compute the unrooted SPR distance. Our algorithm is nearly two orders of magnitude faster than previous methods on small trees, and allows computation of unrooted SPR distances as large as 14 on trees with 50 leaves.