This folder contains the simulation programs written in Python to model the evolution of ideal populations under a set of scenarios, and measure the effective population size using different estimators.
Script that models the evolution of a diploid bi-locus population that evolves with genetic drift and whose genes recombine.
We estimate the effective population size by three different methods:
(1) Decrease in Heterozygosity (He)-based method: for the computation of He we used the method of Nei & Roychoudhury (1974);
(2) Temporal method: for the computation Fc (the change in allele frequencies between two different time samples), we used F estimator developed by Nei and Tajima (1981) and Waples (1989);
(3) Linkage disequilibrium method
N = number of individuals of the population;
generations = number of generations the population is going to evolve;
replicates = number of replicates of the process;
nloc = number of loci;
nall = number of different alleles in each locus;
totall = number of total alleles in the pop in each generation;
rr = recombination rate between each pair of next-to loci;
d = time interval between two samples (for temporal method and NeHe). In general, d=1;
interval = time interval between two samples (for temporal method and NeHe). This can be modified to study the performance of the FcNe and HeNe when time interval is increased;
fr = initial allele frequency of allele 0
Functionalities of NumpyArrays are used.