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CoalMiner: a coalescent model generator for fastsimcoal2
Raya Esplin-Stout1,2, Arun Sethuraman1
1Department of Biology, San Diego State University.
Abstract:
Demographic inference using the Site Frequency Spectrum (SFS) is often constrained by the number and complexity of models tested. Here we present a coalescent model generator called CoalMiner for use with fastsimcoal2. CoalMiner utilizes a decision tree framework to generate biologically plausible models, with user input dictating the number and ranges of demographic parameters and histories, which can then be plugged into the fastsimcoal2 pipeline. Using extensive simulations and empirical data, we show that CoalMiner is an effective helper tool to explore demographic model space. CoalMiner is written in Python and is freely available on GitHub: https://github.com/raywray/coalminer with numerous vignettes and tutorials.
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