# A partial order and cluster-similarity metric on rooted phylogenetic trees

## TL;DR

This paper introduces a new cluster-similarity metric for rooted phylogenetic trees based on a partial order and hierarchy-preserving maps, facilitating easier neighborhood calculations for phylogenetic analysis.

## Contribution

It presents a novel metric on rooted phylogenetic trees using a partial order and hierarchy-preserving maps, improving neighborhood computation for MCMC methods.

## Key findings

- Defines a new cluster-similarity metric based on a partial order.
- Introduces a local operation for easy neighborhood calculation.
- Refines the known hierarchy refinement order.

## Abstract

Metrics on rooted phylogenetic trees are integral to a number of areas of phylogenetic analysis. Cluster-similarity metrics have recently been introduced in order to limit skew in the distribution of distances, and to ensure that trees in the neighbourhood of each other have similar hierarchies. In the present paper we introduce a new cluster-similarity metric on rooted phylogenetic tree space that has an associated local operation, allowing for easy calculation of neighbourhoods, a trait that is desirable for MCMC calculations. The metric is defined by the distance on the Hasse diagram induced by a partial order on the set of rooted phylogenetic trees, itself based on the notion of a hierarchy-preserving map between trees. The partial order we introduce is a refinement of the well-known refinement order on hierarchies. Both the partial order and the hierarchy-preserving maps may also be of independent interest.