Information Theory and Population Genetics

TL;DR

This paper applies information theory to classical population genetics, reinterpreting key results and dynamics such as drift, mutation, and linkage disequilibrium through entropy and mutual information measures.

Contribution

It introduces an information-theoretic framework to analyze population genetics, providing new insights and reformulations of classical results and concepts.

Findings

Reformulation of drift, mutation, and selection in terms of entropy.

Analysis of linkage disequilibrium using mutual information and r^2.

Discussion of hitchhiking within an information-theoretic context.

Abstract

The key findings of classical population genetics are derived using a framework based on information theory using the entropies of the allele frequency distribution as a basis. The common results for drift, mutation, selection, and gene flow will be rewritten both in terms of information theoretic measurements and used to draw the classic conclusions for balance conditions and common features of one locus dynamics. Linkage disequilibrium will also be discussed including the relationship between mutual information and r^2 and a simple model of hitchhiking.