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SimBit: A high performance, flexible and easy-to-use population genetic simulator

Cite this dataset

Matthey-Doret, Remi (2021). SimBit: A high performance, flexible and easy-to-use population genetic simulator [Dataset]. Dryad.


SimBit is a general purpose, high performance forward-in-time population genetics simulator. SimBit can simulate a wide variety of selection scenarios (any selection and dominance coefficients variation, any epistatic interaction, any spatial and temporal changes of selection scenario, etc.), demographic scenarios (any changes in patch sizes, migration rates, realistic demography dependent on fecundity, hard vs. soft selection, exponential vs logistic growth, gametic or zygotic dispersion, etc.) and mating systems (cloning and selfing rates, hermaphrodites or males and females). SimBit can also track QTLs (with hyperdimensional phenotypes, explicit fitness landscape, plasticity, developmental noise, etc.). Finally, SimBit can simulate multiple species with their ecological relationships. SimBit comes with a R wrapper that simplifies the management of an entire research project from the creation of a grid of parameters and corresponding inputs, running simulations and gathering outputs for analysis. SimBit’s performance was extensively benchmarked in comparison to SLiM, Nemo and SFS_CODE, varying population size, recombination rate, mutation rate, and the number of loci. I also reproduced simulations from previous papers, benchmarked QTLs and coalescent tree recording techniques. SimBit was most often the highest performing programs with the only notable exception of SLiM outperforming SimBit in scenarios with few loci and low genetic diversity.



Usage notes

Description details of the simulated scenario are found in the paper and appendix A.


Swiss National Science Foundation, Award: P1SKP3_168393