Population Genetic Simulations

Collected here are a few simple simulations (written in Java) I use (or plan to use) when teaching principles of population genetics in various courses. If you have suggestions for improving them or ideas for other simulations that might be useful, please contact me at kent@darwin.eeb.uconn.edu. I can't promise that I'll have the time to adopt any suggestions you make, but I promise that I'll consider them.
 

• Wahlund effect and F-statistics -- This applet illustrates the Wahlund effect and partitioning of genetic diversity for five populations. Users may select from a variety of allele frequency configurations and several different inbreeding coefficients within populations (all populations are assumed to have the same inbreeding coefficient).
• EM algorithm for ABO frequencies -- This applet illustrates the EM algorithm for estimating allele frequencies in the ABO blood system. Users may select from a variety of sample configurations (including random allocation of phenotypes with three different sample sizes) and several different starting guesses (including random frequencies). Results from each iteration are displayed, but only six iterations can be displayed simultaenously.
• Genetic drift -- This simulation illustrates how allele frequencies change over time as a result of genetic drift in small populations. Users may select from three different starting allele frequenciese (0.1, 0.5, 0.9), five different population sizes (10, 25, 50, 100, 250), and three different numbers of generations for the simulation (50, 100, 250). Results from up to eight simulations are displayed simultaneously in different colors.
• Natural selection -- This simulation illustrates how allele frequencies change over time in response to natural selection on diploid genotypes. Users may select from five different fitnesses (0.8, 0.9, 1.0, 1.1, 1.2) for each of the three genotypes. The number of generations is fixed at 100. Results from up to eight different iterations are displayed simultaneously in different colors.
• Mean fitness -- This applet illustrates the relationship between allele frequency and population mean fitness for a simple one-locus, two-allele model of viability selection. Users may select from a variety of different fitnesses.
• Natural selection and genetic drift -- This simulation illustrates the interaction between natural selection and genetic drift. Users may select from three different starting allele frequencies (0.01, 0.05, 0.1), five different population sizes (10, 25, 50, 100, 250), and three different numbers of generations for the simulation (50, 100, 250). Only a single set of fitnesses representing selection for an initially rare allele are employed, specifically w₁₁ = 1.0, w₁₂ = 0.9, w₂₂ = 0.8.
• Genetic drift and mutation -- This simulation illustrates the interaction between mutation and genetic drift. Users may select from three different population sizes (25, 100, 250) and several different mutation rates (none, 0.0001, 0.001, 0.01). 32 populations are simulated simultaneously and the results are displayed as a frequency histogram.
• Genetic drift and migration -- This simulation illustrates the interaction between migration and genetic drift. Users may select from three different population sizes (25, 100, 250) and several different mutation rates (none, 0.001, 0.01, 0.1). 32 populations are simulated simultaneously and the results are displayed as a frequency histogram.
• t-allele polymorphism -- This simulation illustrates the interaction among drift, selection, and segregation distortion. Users may select from several different population sizes and degrees of distortion. 32 populations are simulated simultaneously and the results are displayed as a frequency histogram.
• Response to selection in a quantitative trait -- This simulation illustrates the response to selection in a quantitative trait. Users may select from several different population means and variances, selective optima and strengths of selection (through the variance of the selection function), and heritabilities. The regression between mid-parent and offspring is shown, individuals surviving a bout of selection are highlighted in blue, and the selective differential and response to selection are highlighted in red.
• Divergence of DNA sequences -- This simulation illustrates divergence of DNA sequences according to two simple models of sequence evolution: Jukes-Cantor and Kimura 2 parameter. Users may select from several different transition/transversion ratios, sequence lengths, and numbers of samples. In addition, the display can illustrate either the percent sequence difference as a function of expected number of substitutions or the calculated distance between two sequences as a function of expected number of substituions.

Note on IE v4.0The Java Virtual Machine in Microsoft's Internet Explorer seems not to understand font selection directives as well as the one in Netscape (or at least my version of Internet Explorer doesn't understand them as well). As a result, tabular displays that line up correctly with a fixed pitch font in Netscape are only approximately lined up with Internet Explorer (yet another reason to prefer Netscape to Explorer).