EASYPOP (Version 1.7): A Computer Program for Population Genetics Simulations

Abstract

If there are many programs for population genetics data analysis, less effort has been devoted to simulation software in this field. However, there are many situations where simulated population genetics datasets would be very useful. Simulations allow exploring situations too complex to be solved analytically. Indeed, outside very simple population genetics models, it is often extremely difficult to obtain the expectations for quantities such as gene correlation or effective size. Simulations also permit us to validate inferences drawn from empirical studies. They can be run with different estimated parameters and compared to the original dataset. It is also possible to build any null hypotheses against which inferences drawn from real data can be tested. Another nice feature of simulated datasets is the possibility of testing new software devoted to population genetics analysis under nontrivial conditions. In addition to their value in research, simulated data can be very useful for educational purposes. Various datasets can be generated and provided to students to train their skills in population genetics data analysis. All these applications prompted me to develop the software EASYPOP, an individual-based model that simulates neutral loci datasets under a very broad range of conditions.