Journal article
Inferring population history with DIY ABC: A user-friendly approach to approximate Bayesian computation
JM Cornuet, F Santos, MA Beaumont, CP Robert, JM Marin, DJ Balding, T Guillemaud, A Estoup
Bioinformatics | OXFORD UNIV PRESS | Published : 2008
Open access
Abstract
Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and popu..
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Awarded by Engineering and Physical Sciences Research Council
Funding Acknowledgements
The development of DIYABC has been supported by a grant from the French Research National Agency (project MISGEPOP) and an EU grant awarded to JMC as an EIF MarieCurie Fellowship (project StatInfPopGen) that allowed him to spend two years in D.J.B.'s Epidemiology and Public Health department at Imperial College (London, UK) where he wrote a major part of this program.