The Concept and Application of Simulation in Population Genetics - Nayak, Sonali Sonejita; Panigrahi, Manjit; Rajawat, Divya; Ghildiyal, Kanika; Jain, Karan; Sharma, Anurodh; Smaraki, Nabaneeta; Jogi, Harsh Rajeshbhai; Bhushan, Bharat (Indian Journal of Veterinary Sciences and Biotechnology, 2023)
The process of building a model or copy of a real-world system and assessing its behaviour under various scenarios is referred to as simulation. Simulations can be used in a variety of fields, including biology, engineering, physics, economics, and the social sciences. Simulation in population genetics is the process of simulating a population's genetic makeup and evolutionary history using mathematical models and computer algorithms. It is important in population genetics for a better understanding of the impact of various evolutionary and demographic scenarios on sequence variation and patterns and for allowing investigators to better assess and design analytical methods in the study of disease-associated genetic factors. This is an important tool for studying population genetic diversity and how natural selection, genetic drift, mutation, migration, and other evolutionary forces have influenced the population's genetic makeup. There are three fundamental frameworks for simulation: coalescent, forward, and resampling methods. Numerous simulators that fit under these frameworks can be compared in terms of their evolutionary and demographic scenarios, computing complexity, and particular applications. Population simulation is becoming increasingly important in evolutionary biology, enabling researchers to explore the effects of various genetic models on genetic diversity and DNA sequence patterns.
Keywords: Coalescence; Evolution; Genomics; Population Genetics; Simulation