Literature DB >> 23749318

Complete numerical solution of the diffusion equation of random genetic drift.

Lei Zhao1, Xingye Yue, David Waxman.   

Abstract

A numerical method is presented to solve the diffusion equation for the random genetic drift that occurs at a single unlinked locus with two alleles. The method was designed to conserve probability, and the resulting numerical solution represents a probability distribution whose total probability is unity. We describe solutions of the diffusion equation whose total probability is unity as complete. Thus the numerical method introduced in this work produces complete solutions, and such solutions have the property that whenever fixation and loss can occur, they are automatically included within the solution. This feature demonstrates that the diffusion approximation can describe not only internal allele frequencies, but also the boundary frequencies zero and one. The numerical approach presented here constitutes a single inclusive framework from which to perform calculations for random genetic drift. It has a straightforward implementation, allowing it to be applied to a wide variety of problems, including those with time-dependent parameters, such as changing population sizes. As tests and illustrations of the numerical method, it is used to determine: (i) the probability density and time-dependent probability of fixation for a neutral locus in a population of constant size; (ii) the probability of fixation in the presence of selection; and (iii) the probability of fixation in the presence of selection and demographic change, the latter in the form of a changing population size.

Keywords:  allele fixation; demographic change, Wright–Fisher model; diffusion analysis; forward diffusion equation; numerical scheme

Mesh:

Year:  2013        PMID: 23749318      PMCID: PMC3730923          DOI: 10.1534/genetics.113.152017

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  13 in total

1.  On the probability of fixation of mutant genes in a population.

Authors:  M KIMURA
Journal:  Genetics       Date:  1962-06       Impact factor: 4.562

2.  Stochastic processes and distribution of gene frequencies under natural selection.

Authors:  M KIMURA
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3.  Serial founder effects during range expansion: a spatial analog of genetic drift.

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4.  Comparison and content of the Wright-Fisher model of random genetic drift, the diffusion approximation, and an intermediate model.

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5.  A novel solution for the time-dependent probability of gene fixation or loss under natural selection.

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Journal:  Genetics       Date:  2004-10       Impact factor: 4.562

6.  Evolution in Mendelian Populations.

Authors:  S Wright
Journal:  Genetics       Date:  1931-03       Impact factor: 4.562

7.  Singular solutions of the diffusion equation of population genetics.

Authors:  A J McKane; D Waxman
Journal:  J Theor Biol       Date:  2007-04-27       Impact factor: 2.691

8.  The fixation probability of rare mutators in finite asexual populations.

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Journal:  Genetics       Date:  2009-01-19       Impact factor: 4.562

9.  Efficient simulation under a population genetics model of carcinogenesis.

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10.  A unified treatment of the probability of fixation when population size and the strength of selection change over time.

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Journal:  Genetics       Date:  2011-04-28       Impact factor: 4.562

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  8 in total

1.  Inference Under a Wright-Fisher Model Using an Accurate Beta Approximation.

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Journal:  Genetics       Date:  2015-08-26       Impact factor: 4.562

2.  Transition Densities and Sample Frequency Spectra of Diffusion Processes with Selection and Variable Population Size.

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Journal:  Genetics       Date:  2015-04-14       Impact factor: 4.562

Review 3.  Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data.

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5.  A path integral formulation of the Wright-Fisher process with genic selection.

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6.  Wright-Fisher exact solver (WFES): scalable analysis of population genetic models without simulation or diffusion theory.

Authors:  Ivan Krukov; Bianca de Sanctis; A P Jason de Koning
Journal:  Bioinformatics       Date:  2017-05-01       Impact factor: 6.937

7.  Allele Age Under Non-Classical Assumptions is Clarified by an Exact Computational Markov Chain Approach.

Authors:  Bianca De Sanctis; Ivan Krukov; A P Jason de Koning
Journal:  Sci Rep       Date:  2017-09-19       Impact factor: 4.379

8.  Inference of Selection from Genetic Time Series Using Various Parametric Approximations to the Wright-Fisher Model.

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Journal:  G3 (Bethesda)       Date:  2019-12-03       Impact factor: 3.154

  8 in total

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