A master equation approach to the n-coalescent problem

TL;DR

This paper introduces a simplified master equation approach to the n-coalescent problem, enabling easier computation of ancestral tree properties in evolutionary models like Wright-Fisher and Moran.

Contribution

It shifts focus from the coalescent time to the joint variable of ancestors and time, providing a general, straightforward solution for various models.

Findings

Derived a master equation for the joint probability P(n,t)

Solved the equation for both continuous and discrete time models

Enabled computation of coalescent times and tree topologies

Abstract

Given an evolutionary model, such as Wright--Fisher (WF) or Moran, the n-coalescent problem consists of going backward in time to find for example the time to the most recent common ancestor (MRCA) and the topology of the tree. In the literature, this problem is tackled mostly by computing directly the random variable t, time to reach the MRCA. I show here that by shifting the focus from the random variable t to the joined variable (n,t), where n is the number of ancestors at time t, the problem is greatly simplified. Indeed, P(n,t), the probability of this variable, obeys a simpler master equation that can be solved in a straightforward way for the most general model. This probability can then be used to compute relevant information of the n-coalescent, for both random variables $t_{n}$ (random time to reach a given state n) and $n_{t}$ (random number of ancestors at a given time t). The cumulative distribution function for $t_{1}$ for example is $P(1,t)$. I give in this article the general solution for continuous time models such as Moran and discrete time ones such as WF.