Diffusion Theory


The mathematical description of the process of diffusion has proved a powerful tool for describing how deterministic forces, such as mutation, selection and migration, and the stochastic process of genetic drift interact to influence the fate of mutations in populations.

Keywords: diffusion; allele; mutation; drift; selection

Figure 1.

Graphical depiction of the Kolmogorov forward and backward diffusion equations. The forward equation (a) considers how events just before the time of interest affect the probability density, while the backward equation (b) is concerned with events occurring just after the start of the process.

Figure 2.

Wright's distribution of allele frequencies under the infinite‐alleles mutation model.

Figure 3.

Distribution of allele frequencies of human leukocyte antigen‐A alleles from a sample of 228 European caucasoids (data from Cavalli‐Szforza and Bodmer ), and the expected distribution given the observed number of alleles (θ=3.76). Using sample homozygosity (eqn []) as a test statistic, we can reject the standard neutral model at P<0.05.



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Further Reading

Gillespie JH (1998) Population genetics: A Concise Guide. Baltimore/London: The Johns Hopkins University Press.

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McVean, Gil(Jul 2006) Diffusion Theory. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1038/npg.els.0005466]