The consequences of not accounting for background selection in demographic inference

Recently, there has been increased awareness of the role of background selection (BGS) in both data analysis and modelling advances. However, BGS is still difficult to take into account because of tractability issues with simulations and difficulty with nonequilibrium demographic models. Often, simple rescaling adjustments of effective population size are used. However, there has been neither a proper characterization of how BGS could bias or shift inference when not properly taken into account, nor a thorough analysis of whether rescaling is a sufficient solution. Here, we carry out extensive simulations with BGS to determine biases and behaviour of demographic inference using an approximate Bayesian approach. We find that results can be positively misleading with significant bias, and describe the parameter space in which BGS models replicate observed neutral nonequilibrium expectations.


Published in:
Molecular Ecology, 25, 1, 135-141
Year:
2016
Publisher:
Hoboken, Wiley-Blackwell
ISSN:
0962-1083
Keywords:
Laboratories:




 Record created 2016-02-16, last modified 2018-03-17


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