A sequentially Markov conditional sampling distribution for structured populations with migration and recombination

TL;DR

This paper extends the sequentially Markov conditional sampling distribution to structured populations with migration and recombination, enabling more accurate population genetic analyses.

Contribution

It introduces a new CSD framework that incorporates population subdivision, migration, and recombination, with practical applications in estimating migration rates.

Findings

Accurately estimates a wide range of migration rates

Provides a genealogical interpretation related to the structured coalescent

Offers an efficient computational approach for structured populations

Abstract

Conditional sampling distributions (CSDs), sometimes referred to as copying models, underlie numerous practical tools in population genomic analyses. Though an important application that has received much attention is the inference of population structure, the explicit exchange of migrants at specified rates has not hitherto been incorporated into the CSD in a principled framework. Recently, in the case of a single panmictic population, a sequentially Markov CSD has been developed as an accurate, efficient approximation to a principled CSD derived from the diffusion process dual to the coalescent with recombination. In this paper, the sequentially Markov CSD framework is extended to incorporate subdivided population structure, thus providing an efficiently computable CSD that admits a genealogical interpretation related to the structured coalescent with migration and recombination. As a concrete application, it is demonstrated empirically that the CSD developed here can be employed to yield accurate estimation of a wide range of migration rates.