ΔΔCt vs Pfaffl: primer efficiency and efficiency correction
ΔΔCt assumes every primer pair exactly doubles its product each cycle. When the real efficiency differs, the Pfaffl method plugs each gene’s measured efficiency into the calculation.
Enter efficiencies (%) and get Pfaffl-corrected results instantly, side by side with ΔΔCt.
Open the qPCR tool →1. Measuring efficiency: the standard curve
Make about five 10-fold dilutions of cDNA, measure Ct, and fit a line with x = log10(amount), y = Ct. The slope gives the efficiency.
| Slope | E | Efficiency | Verdict |
|---|---|---|---|
| −3.32 | 2.00 | 100% | Ideal |
| −3.10 | 2.10 | 110% | Near upper limit |
| −3.58 | 1.90 | 90% | Near lower limit |
A good primer pair usually has 90–110% efficiency and R² ≥ 0.98.
2. The Pfaffl equation
It is the ΔΔCt formula with the “2” replaced by each gene’s measured E. If both efficiencies are 2, the result equals 2−ΔΔCt. With several reference genes, use the geometric mean of their terms in the denominator.
3. How much does efficiency matter?
Take the example from the ΔΔCt guide (control IL6 28.4 → LPS 24.4, GAPDH 18.2 → 18.3) and assume IL6 efficiency 90% (E = 1.90) and GAPDH 100% (E = 2.00).
- Target: 1.90(28.4 − 24.4) = 1.904.0 ≈ 13.0
- Reference: 2.00(18.2 − 18.3) = 2−0.1 ≈ 0.93
- Pfaffl ratio ≈ 13.0 ÷ 0.93 ≈ 14.0-fold (ΔΔCt gave 17.1-fold)
A 10% efficiency difference changed the result by about 20%. The larger the Ct difference, the bigger the effect.
4. Which one to use
- Efficiency not measured → ΔΔCt. It is the most widely used, and most commercial primers are validated near 100%.
- Efficiency measured with a standard curve and genes differ a lot → Pfaffl.
- Either way, state the method (and the efficiencies for Pfaffl) in your Methods; the MIQE guidelines recommend reporting efficiency.
Enter efficiencies (%) and get Pfaffl-corrected results instantly, side by side with ΔΔCt.
Open the qPCR tool →