The assumption of weak selection simplifies mathematical models in population genetics
Mathematical models in population genetics frequently invoke the assumption of weak selection (or weak epistasis) to make complex evolutionary dynamics analytically tractable, such as by ignoring linkage disequilibrium or deriving polynomial-time fixation probabilities.
The claim is a specific, well-accepted methodological principle in population genetics where assumptions like weak selection or weak epistasis are routinely used to simplify intractable mathematical models (e.g., ignoring linkage disequilibrium or using perturbation methods). Multiple retrieved papers explicitly demonstrate or rely on this approach to make complex systems mathematically tractable.
Benjamin Allen, C. Sample, P. Steinhagen, Julia Shapiro, Matthew S. King, Timothy Hedspeth, M. Gonçalves. Fixation probabilities in graph-structured populations under weak selection. 2021. https://doi.org/10.1371/journal.pcbi.1008695
Paper [3] derives tractable expressions for fixation probabilities by assuming weak selection, enabling computations on arbitrary graphs.
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Martin Pontz, J. Hofbauer, R. Bürger. Evolutionary dynamics in the two-locus two-allele model with weak selection. 2017. https://doi.org/10.1007/s00285-017-1140-7
Paper [4] uses weak selection to ignore linkage disequilibrium, making complex two-locus two-allele models analytically tractable.
Alan Hastings. MULTILOCUS POPULATION GENETICS WITH WEAK EPISTASIS. II. EQUILIBRIUM PROPERTIES OF MULTILOCUS MODELS: WHAT IS THE UNIT OF SELECTION?. 1986. https://doi.org/10.1093/genetics/112.1.157
Paper [5] applies perturbation techniques with weak epistasis to simplify multilocus models and determine equilibrium properties.
Alan Hastings. MULTILOCUS POPULATION GENETICS WITH WEAK EPISTASIS. I. EQUILIBRIUM PROPERTIES OF TWO-LOCUS TWO-ALLELE MODELS. 1985. https://doi.org/10.1093/genetics/109.4.799
Paper [6] employs weak epistasis and overdominance assumptions to determine tractable equilibrium properties in two-locus models.
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