What does the Wright–Fisher simulation show?

It shows allele-frequency trajectories across replicate populations, the distribution of final frequencies, heterozygosity decay, and fixation probability.

What is the role of population size N?

N sets the number of individuals. In diploids, the model uses 2N gene copies; smaller populations generally show stronger random drift.

Can I model natural selection and mutation?

Yes. Set mutation rate μ and selection coefficient s, then choose dominant, recessive, or additive dominance for allele A.

What does a random seed do?

A seed makes the stochastic simulation deterministic, so the same settings and seed can reproduce the same result.

How do I run the Hardy–Weinberg test?

Enter the observed counts for AA, Aa, and aa. The tool uses these genotype counts for a Hardy–Weinberg equilibrium chi-square test.

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Wright–Fisher Population Drift & Allele Frequency Tutor

Simulate Wright–Fisher genetic drift across many replicate populations with mutation and selection. Visualize drift trajectories, the final-frequency distribution, heterozygosity decay Hₜ = H₀(1−1/2Nₑ)ᵗ, and run a Hardy–Weinberg chi-square test.

Details

What this tool helps you do

An interactive tutor for the Wright–Fisher model — the canonical null model of random genetic drift. Set a population size N (diploid 2N or haploid N gene copies), an initial allele frequency p₀, an optional mutation rate μ and selection coefficient s with dominant/recessive/additive dominance, then run many replicate populations in parallel. The tool plots every replicate trajectory, the distribution of final frequencies (showing how often A fixes vs is lost), the observed mean heterozygosity against the analytic decay Hₜ = H₀(1 − 1/(2Nₑ))ᵗ, and Kimura's theoretical fixation probability. Optionally paste genotype counts (AA/Aa/aa) to run a Hardy–Weinberg equilibrium chi-square test. Bridges the gap between a single Mendelian Punnett cross and the long-run population-level fate of an allele. Deterministic per seed.

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2 examples

Neutral drift: N=100, p₀=0.5, 100 generations, 40 reps

Pure neutral Wright–Fisher drift in a diploid population of 100 (200 gene copies). A should fix ~50% of the time and be lost ~50% of the time; heterozygosity decays as H₀(1−1/2Nₑ)ᵗ.

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Selection sweeps allele A: s=0.1 in N=200

Additive selection favouring A (s=0.1) in a diploid population of 200. A should fix much more often than the neutral p₀=0.3 prediction; Kimura's diffusion approximation gives the theoretical fixation probability.

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Inputs

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12 options

SettingsAdjust formats, ranges, numbers, and modes.12

Population size (N individuals)numberOptionalPloidyselectOptionalGenerationsnumberOptionalReplicate populationsnumberOptionalInitial frequency of allele A (p₀)numberOptionalMutation rate μ (per gene per generation)numberOptionalSelection coefficient s (>0 favours A)numberOptionalDominance of AselectOptionalRandom seed (reproducibility)numberOptionalHardy–Weinberg test — AA count (optional)numberOptionalHardy–Weinberg test — Aa count (optional)numberOptionalHardy–Weinberg test — aa count (optional)numberOptional

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Wright–Fisher Population Drift & Allele Frequency Tutor

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Examples

1. Neutral drift from an intermediate allele frequency

2. Selection favoring allele A

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