qPCR Efficiency Calculator
Enter the slope of the qPCR standard curve to compute amplification efficiency E = 10^(−1/slope) − 1, evaluating reaction performance and whether the standard curve is ideal.
Input Data
Results
At a glance:qPCR (real-time quantitative PCR) amplification efficiency E describes how much template doubles each cycle. For a perfect doubling reaction, the amount rises 2-fold per cycle (E = 1, i.e. 100%). The relationship with the standard-curve slope is E = 10^(−1/slope) − 1: when slope = −3.32, E = 1 exactly (100%); efficiency in percent = E × 100%. Ideal qPCR efficiency is about 90–110% (slope −3.6 to −3.1). A slope shallower than −3.1 (E > 110%) usually suggests primer dimer or template contamination causing extra signal; steeper than −3.6 (E < 90%) indicates inhibition, poor primer matching, or pipetting errors. Efficiency is the basis for ΔΔCt relative quantification accuracy, so checking it is a required step before running a qPCR experiment.
Formula
Amplification efficiency: E = 10^(−1/slope) − 1.
Percent efficiency: %E = E × 100%.
Ideal slope ≈ −3.32 (E = 100%); acceptable 90–110% (slope −3.6 to −3.1).
$$E = 10^{-1/\text{slope}} - 1$$$$\%E = E \times 100\%$$How to Use
- Run a standard curve across several template concentrations and fit Ct vs log₁₀ concentration.
- Enter the fitted slope (negative) into this tool.
- The right panel shows efficiency E, percentage, and fold increase per cycle; judge whether the reaction is ideal.
Slope vs qPCR efficiency correspondence
| Slope | Efficiency E | Interpretation |
|---|---|---|
| −3.1 | 1.10 (110%) | Upper limit of ideal |
| −3.32 | 1.00 (100%) | Perfect doubling, ideal |
| −3.6 | 0.90 (90%) | Lower limit of ideal |
| −2.8 | 1.28 (128%) | Too high: dimer/contamination |
| −4.0 | 0.78 (78%) | Too low: inhibition/primer issue |
Best practice is 90–110% efficiency; otherwise optimize primers, annealing temperature, or template purity before relative quantification.
Case Studies
Ideal standard curve
A qPCR standard curve gives slope = −3.32.
E = 10^(−1/−3.32) − 1 = 10^0.3012 − 1 ≈ 1.0, i.e. 100%.
The reaction doubles each cycle — an ideal, well-optimized qPCR assay.
Suspiciously high efficiency (primer dimer)
Another assay gives slope = −2.8 (E > 100%).
E = 10^(−1/−2.8) − 1 = 10^0.357 − 1 ≈ 1.276, i.e. 127.6%, exceeding the 110% upper limit.
Suggests primer dimer or contamination inflating signal; redesign primers or optimize annealing temperature and re-run the validation.
FAQ
How is efficiency related to the standard-curve slope?
Because Ct changes linearly with log₁₀ template: Ct = −(1/slope)·log₁₀N + b. Each 10-fold concentration change shifts Ct by the slope; since one cycle of perfect doubling is a 10^(−1/slope) factor, efficiency E = 10^(−1/slope) − 1. Slope −3.32 → E = 100%.
What is ideal qPCR efficiency?
About 90–110% (slope roughly −3.6 to −3.1), ideally 100% (slope −3.32). Within this range the reaction doubles stably with little bias, and ΔΔCt relative quantification is reliable. Outside it, quantification error grows.
Why is efficiency >110% suspicious?
Over 110% means more than 2-fold increase per cycle, impossible for a single-target amplification, usually caused by primer dimers, non-specific products, or template contamination adding extra signal at high cycle numbers — inflating apparent efficiency. Optimize primers/annealing temperature and revalidate.
Why is efficiency <90% a problem?
Below 90% means the reaction is suppressed, common with PCR inhibitors in the sample, poor primer-template matching, or pipetting/reagent errors. Low efficiency biases quantification and lowers sensitivity; remove inhibitors or re-optimize the reaction.
How does efficiency affect ΔΔCt?
The classic ΔΔCt formula assumes E = 100% for all genes; if E differs, use the efficiency-corrected form: ratio = (E_target)^ΔCt_target ÷ (E_ref)^ΔCt_ref. So verifying each gene's efficiency is a prerequisite for accurate relative quantification.
Related Tools
References
Content review: Calculatorism Science Team. Results are for reference only; please refer to the relevant authorities for the official figures.