qPCR Efficiency Calculator
Written by Thierno Sadou Diallo, formula verified per our methodology • Last checked on 9/9/2026
A qPCR's efficiency is calculated with E (%) = (10^(−1/slope) − 1) × 100. An ideal slope of −3.32 gives an efficiency close to 100%, corresponding to an exact doubling of DNA at each amplification cycle.
Explanation
Amplification efficiency is an essential quality control for any quantitative PCR (qPCR) experiment: it measures whether the amount of DNA properly doubles at each cycle, the assumption underlying any relative or absolute quantification by this technique. It's derived from the standard curve's slope, obtained by plotting the threshold cycle (Ct) measured for a series of dilutions against the base-10 logarithm of their concentration: the more efficiently DNA doubles at each cycle, the closer this slope gets to the theoretical value of −3.32 (since log₁₀(2) ≈ 0.301, the reciprocal of 3.32). The formula E = (10^(−1/slope) − 1) × 100 converts this slope into a directly interpretable percentage. In practice, an efficiency between 90% and 110% (a slope between about −3.58 and −3.10) is generally considered acceptable for most qPCR applications; outside this range, the reliability of the quantification can be compromised, and it's recommended to check primer quality, the presence of inhibitors, or the accuracy of the standard dilution series. An efficiency above 100% doesn't indicate "better than perfect" amplification, but most often a technical artifact (imprecise pipetting of the dilution series, presence of primer dimers). To amplify a target before evaluating its efficiency, see our PCR amplification calculator; to quantify the starting DNA or RNA concentration, our nucleic acid concentration calculator.
Example: a standard curve slope of −3.32
Inputs
Slope: −3.32.
Calculation
Efficiency = (10^(−1 ÷ −3.32) − 1) × 100 = (10^0.301 − 1) × 100 ≈ (2.0007 − 1) × 100 ≈ 100.1%.
Result
This slope corresponds to an amplification efficiency of about 100%, close to the theoretical ideal.
Frequently asked questions
Why is the ideal slope exactly −3.32?
Because log₁₀(2) ≈ 0.301, and 1 ÷ 0.301 ≈ 3.32. If the amount of DNA doubles exactly at each cycle (100% efficiency), about 3.32 extra cycles are needed to compensate for each tenfold dilution (factor of 10) in the standard series — hence the theoretical slope of −3.32 on the graph of Ct versus log₁₀ of concentration.
What should I do if my efficiency falls outside the 90-110% range?
First check the accuracy of your standard curve's serial dilutions (a systematic pipetting error directly skews the slope), the specificity and quality of the primers (presence of dimers, poor annealing), and the possible presence of PCR inhibitors in the sample. An out-of-range efficiency doesn't make the qPCR unusable, but calls for caution when interpreting quantitative results, especially for absolute quantification.
Does this calculation replace the standard curve's coefficient of determination (R²)?
No, these are two complementary but distinct quality controls. The slope (and the efficiency it gives) measures amplification performance at each cycle; R² measures the linearity of the relationship between Ct and log₁₀(concentration), i.e. the reliability of the curve itself across the whole range of dilutions tested. A good qPCR generally requires an efficiency close to 100% and an R² close to 1.