Variance Components Calculator
Use variance estimates to compute H² and h².
H² = VG / VP | h² = VA / VP
Enter values and click calculate.
Heritability Calculator (H² & h²)
Estimate broad-sense heritability, narrow-sense heritability, and realized heritability from your data. Designed for students, researchers, breeders, and anyone working with quantitative genetics.
Realized Heritability Calculator
Estimate realized narrow-sense heritability from a selection experiment.
h² = R / S
Enter R and S to estimate realized heritability.
Heritability Calculator Guide: Meaning, Formulas, Interpretation, and Practical Use
Heritability is one of the most discussed concepts in genetics, breeding, and evolutionary biology. It helps answer a practical question: how much of the observed variation in a trait is associated with genetic differences in a specific population and environment? This page gives you a working heritability calculator and a complete guide to understanding what your results do—and do not—mean.
In this guide
What is heritability?
Heritability is a population-level statistic. It does not describe an individual person, animal, or plant. Instead, it quantifies the proportion of total phenotypic variation attributable to genetic variation within a given population under specific environmental conditions.
If a trait has high heritability in one setting, that does not guarantee the same value in another setting. Change the environment, sample composition, or measurement quality, and heritability can change substantially.
Broad-sense (H²) vs narrow-sense (h²) heritability
Broad-sense heritability (H²) includes all genetic variance sources: additive, dominance, and epistatic effects. It is useful when you want to understand total genetic contribution to trait variance.
Narrow-sense heritability (h²) includes only additive genetic variance. This is often the most useful measure in breeding because additive effects are predictably passed from parents to offspring and therefore determine response to selection.
| Measure | Formula | Includes | Typical use |
|---|---|---|---|
| Broad-sense H² | VG/VP | VA + VD + VI | Total genetic contribution |
| Narrow-sense h² | VA/VP | Additive variance only | Selection and breeding response |
| Realized h² | R/S | Observed selection outcome | Experimental selection programs |
Formulas used by this Heritability Calculator
In the variance components calculator:
VG = VA + VD + VI
VP = VG + VE + VG×E
H² = VG / VP h² = VA / VP
In the realized heritability calculator:
h² = R / S
Where R is the response to selection and S is the selection differential.
How to interpret heritability values
As a simple rule of thumb for narrow-sense heritability:
- Low: below 0.20 — environment and/or non-additive factors play a large role in observed variation.
- Moderate: 0.20 to 0.40 — meaningful additive genetic signal is present.
- High: above 0.40 — stronger expected response to selection, all else equal.
These cutoffs are context-dependent. A value considered “high” in one species or trait may be ordinary in another. Always interpret estimates alongside confidence intervals, sample size, and study design quality.
Worked examples
Example 1: Variance components. Suppose VA=18.5, VD=4.0, VI=2.5, VE=21.5, VG×E=3.5. Then VG=25.0 and VP=50.0. So H²=0.50 and h²=0.37. Interpretation: total genetic contribution is substantial, and additive effects are moderate-to-high, suggesting useful progress from selection.
Example 2: Realized heritability. If the selection differential is S=12 and the observed response is R=4.8, then h²=0.40. This indicates a moderate-to-strong additive component under those specific selection conditions.
Common mistakes and limitations
1) Treating heritability as fixed. Heritability is not a universal constant for a trait. It changes by population, environment, age, and measurement method.
2) Confusing heritability with immutability. A high heritability value does not mean a trait cannot be changed by environment or intervention.
3) Ignoring measurement error. Poor phenotype measurement inflates environmental variance and can distort estimates.
4) Overlooking G×E. Genotype-by-environment interaction can be substantial and may affect both interpretation and practical prediction.
5) Extrapolating across groups. Estimates from one breed, line, population, or ecological context should not be directly transferred to another without validation.
Best practices for better estimates
- Use reliable, repeatable phenotyping protocols.
- Increase sample size and include replication where possible.
- Model fixed effects (sex, age, batch, site, season) appropriately.
- Check assumptions of the statistical framework you use.
- Report uncertainty (confidence intervals or credible intervals).
- Interpret heritability alongside genetic correlations and selection goals.
Frequently asked questions
Does high heritability mean environment is unimportant?
No. High heritability only indicates that, in your current data context, genetic differences explain a larger share of variation. Environmental interventions may still have strong effects.
Can heritability be greater than 1?
In theory, true heritability is between 0 and 1. Estimates outside this range usually indicate sampling error, model misspecification, or noisy variance estimates.
Which measure should breeders use?
Narrow-sense heritability (h²) is usually most relevant for predicting response to selection because additive effects are transmitted most predictably.
What if my realized h² is negative?
Negative realized values can occur due to random noise, weak selection, small sample size, or changing environments across generations. Review data quality and design.
Does this calculator replace mixed-model analysis?
No. It is a fast, practical estimator. Formal inference for publication or decision-critical programs should use appropriate quantitative genetic models and uncertainty estimates.
Educational note: This calculator provides point estimates for planning and learning. For scientific reporting, include robust statistical modeling, uncertainty intervals, and transparent assumptions.