Dynamic Geodesics in Treespace via Parametric Maximum Flow

TL;DR

This paper introduces an algorithm for efficiently updating shortest paths in treespace when endpoints change, leveraging parametric sensitivity analysis of maximum flow problems, which benefits statistical and phylogenetic analyses.

Contribution

It presents a novel method for dynamic geodesic updates in treespace using parametric maximum flow analysis, improving efficiency for optimization tasks.

Findings

Algorithm efficiently updates geodesics with endpoint changes.

Method enables faster optimization in phylogenetic analysis.

Supports dynamic statistical analysis of tree populations.

Abstract

Shortest paths in treespace, which represent minimal deformations between trees, are unique and can be computed in polynomial time. The ability to quickly compute shortest paths has enabled new approaches for statistical analysis of populations of trees and phylogenetic inference. This paper gives a new algorithm for updating geodesic paths when the end points are dynamic. Such algorithms will be especially useful when optimizing for objectives that are functions of distances from a search point to other points e.g. for finding a tree which has the minimum average distance to a collection of trees. Our method for updating treespace shortest paths is based on parametric sensitivity analysis of the maximum flow subproblems that are optimized when solving for a treespace geodesic.