A Duality Approach to the Genealogies of Discrete Non-Neutral Wright-Fisher Models

TL;DR

This paper extends the duality concept to discrete non-neutral Wright-Fisher models with monotone bias probabilities, providing new formulae and evolutionary mechanisms for population genetics analysis.

Contribution

It demonstrates the applicability of duality in non-neutral models and introduces novel evolutionary mechanisms using algebraic properties of monotone functions.

Findings

Duality formulae are effective for non-neutral Wright-Fisher models.

Most classical bias probabilities are within the CM class or can be adapted to it.

New evolutionary mechanisms are proposed and discussed.

Abstract

Discrete ancestral problems arising in population genetics are investigated. In the neutral case, the duality concept has proved of particular interest in the understanding of backward in time ancestral process from the forward in time branching population dynamics. We show that duality formulae still are of great use when considering discrete non-neutral Wright-Fisher models. This concerns a large class of non-neutral models with completely monotone (CM) bias probabilities. We show that most classical bias probabilities used in the genetics literature fall within this CM class or are amenable to it through some `reciprocal mechanism' which we define. Next, using elementary algebra on CM functions, some suggested novel evolutionary mechanisms of potential interest are introduced and discussed.