Coalescent simulation in continuous space

Jerome Kelleher, Nicholas H Barton, Alison M Etheridge

Research output: Contribution to journalArticlepeer-review

Abstract

Coalescent simulation has become an indispensable tool in population genetics, and many complex evolutionary scenarios have been incorporated into the basic algorithm. Despite many years of intense interest in spatial structure, however, there are no available methods to simulate the ancestry of a sample of genes that occupy a spatial continuum. This is mainly due to the severe technical problems encountered by the classical model of isolation by distance. A recently introduced model solves these technical problems and provides a solid theoretical basis for the study of populations evolving in continuous space. We present a detailed algorithm to simulate the coalescent process in this model, and provide an efficient implementation of a generalized version of this algorithm as a freely available Python module.
Original languageEnglish
Pages (from-to)955-956
Number of pages2
JournalBioinformatics
Volume29
Issue number7
DOIs
Publication statusPublished - 2013

Fingerprint Dive into the research topics of 'Coalescent simulation in continuous space'. Together they form a unique fingerprint.

Cite this