Population-genetic models begin from the perspective that the factors that affect the genealogical descent of a disease mutation — such as migrations, changes in population size, natural selection, and local recombination landscape — ultimately affect the distribution of the mutation across individuals in the present. Because the full genetic history of the human population is unknown, population-genetic models based on relatively few parameters can be used instead to simulate plausible histories, to examine the properties of risk variants simulated under the models, and to evaluate strategies for detecting these variants. Many of these models use the coalescent framework 96,97, which provides a flexible, computationally efficient, and theoretically grounded approach that can simulate one or more populations retrospectively, back in time from the present.
