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Scaling the Gene Duplication Problem Towards the Tree of Life

The gene duplication problem seeks the species tree that implies the fewest duplications across a collection of gene trees. We describe two new improvements to existing heuristics that greatly accelerate the rSPR local search. The improvements involve (i) reducing the computational complexity by Θ(n/h) for sequential evaluations of the reconciliation cost on n taxa and a tree height of h, and (ii) a lightweight and effective heuristic search strategy. In analyses of both empirical and simulated data sets, the new improvements display tremendous speedup from the best existing heuristics with no apparent loss of accuracy. We also demonstrate with simulated data that the improved heuristics can easily compute species trees with 100,000 taxa on a single desktop processor.