Estimate allele frequencies from genotype counts with accuracy and clarity. Enter sample numbers to calculate p and q plus Hardy Weinberg expectations. Get instant validation tips visual summaries and explanations for teaching research and quality control. Designed for labs classrooms and fieldwork with mobile friendly layout. Accessible offline printable and easy to integrate anywhere.
Enter the observed genotype counts for AA, Aa, and aa. Optionally rename the alleles to your preferred symbols. Set your desired decimal precision, then press Calculate. The tool reports allele frequencies p and q, genotype frequencies, Hardy–Weinberg expectations, a chi square test, and a confidence interval for p.
For small expected counts below five, chi square approximations may be conservative. Consider exact tests or combine classes when appropriate. Always interpret deviations in the context of sampling, structure, selection, and genotyping quality.
Total individuals: N = n_{AA} + n_{Aa} + n_{aa}. Total alleles: m = 2N.
Allele frequencies: p = (2·n_{AA} + n_{Aa}) / (2N), q = 1 - p.
Under Hardy–Weinberg equilibrium, expected genotype frequencies are p², 2pq, q², so expected counts are N·p², 2N·pq, N·q².
Goodness of fit: \chi^2 = Σ (O - E)^2 / E with df ≈ 1 when estimating p from data. Two sided p value uses 1 - \mathrm{erf}(\sqrt{\chi^2/2}) for df=1.
Uncertainty: 95% Wilson interval for p based on m = 2N allele trials.
Enter genotype counts and press Calculate to view results.
It is the proportion of a specific allele among all allele copies at a locus in a population. With bi allelic loci there are two values p and q that sum to one.
Many studies record genotypes. From genotype counts you can reconstruct allele counts via 2·n(AA) + n(Aa) and 2·n(aa) + n(Aa).
Large randomly mating population with no selection mutation migration or drift at the locus and accurate genotyping. Violations can cause deviations from the expected p² 2pq q² proportions.
A small p value suggests observed genotype distribution differs from equilibrium expectations. Investigate sampling error structure related mating selection or technical artifacts before drawing biological conclusions.
Allele frequency estimates are subject to sampling variability. The Wilson interval provides robust coverage for binomial proportions using the total number of allele copies as trials.
Yes. Change the two allele labels to any short symbols. Results and formulas update automatically including genotype labels and frequency interpretations.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.