A Generalized Robinson-Foulds Distance for Clonal Trees, Mutation Trees, and Phylogenetic Trees and Networks

Cancer evolution is often modeled by clonal trees (whose nodes are labeled by multiple somatic mutations) or mutation trees (where nodes are labeled by single somatic mutations). Clonal trees are generated from sequence data with different computational methods that may produce different clone phylogenies, rendering their analysis and comparison necessary to infer mutation order and clone origin during tumor progression. In this paper, we present a distance metric for multi-labeled trees that generalizes the Robinson-Foulds distance for phylogenetic trees, allows for a similarity assessment at much higher resolution, and can be applied to trees and networks with different sets of node labels. The generalized Robinson-Foulds distance can be computed in time quadratic in the size of the input multisets of multisets of node labels, and is a metric for clonal trees, mutation trees, phylogenetic trees, and several classes of phylogenetic networks.