Appendix 1—figure 1. Validating the SLiM engine backend under a genetic map.

Here, we validate our integration of the SLiM (Haller et al., 2019; Haller and Messer, 2019) engine backend. We show quantile-quantile plots between SLiM and msprime engines for three population genetic summary statistics: r², Tajima’s $\pi$, and Tajima’s D. Additionally, we show runtimes for generating each simulation replicate. Data were generated by simulating 100 replicates of human chromosome 22 under the AncientEurasia_9K19 model (Kamm et al., 2019) using the HapMapII_GRCh37 genetic map (Frazer et al., 2007). 12 samples were drawn from each population (excluding basal Eurasians). From top to bottom, we show results using three scaling factors for the population sizes: Q = 1, Q = 10, and Q = 50. Kolmogorov-Smirnov two-sample test statistics (D) and p-values are shown, testing the null hypothesis that the quantiles were drawn from the same continuous distribution.