qPCR Efficiency Calculator

Calculate qPCR efficiency from slope or amplification factor

Edit any field to solve the others instantly.

Last updated: December 30, 2025

CreatorFrank Zhao

Calculation Mode

Slope

More info

Amplification factor

More info

qPCR efficiency

More info

1qPCR efficiency

E = -1 + 10^{-1/\text{slope}}

2Amplification factor

A = 10^{-1/\text{slope}}

3Link between A and E

E = A - 1

slopeStandard curve slope

AAmplification factor

EEfficiency (decimal)

E%Efficiency (percent)

10Base-10 exponent

logNatural log in solver

TOC

This guide explains what qPCR efficiency means, how the calculator computes it, and what you can do when your result is outside the usual targets. If you’re still dialing in basic PCR conditions (especially primer binding), start with our Annealing Temperature Calculator.

Use this qPCR efficiency calculator to estimate assay performance from the slope of a standard curve. A perfectly efficient reaction doubles the target each cycle, which corresponds to an efficiency of $100\%$ . In practice, many labs treat roughly $90\%\text{ to }110\%$ as a healthy range (with $100\%$ as the ideal).

→What is qPCR efficiency?
→How to calculate qPCR efficiency — Formula
→How to use the qPCR efficiency calculator — Example
→How to optimize PCR efficiency and dilution curves
→FAQs

What is qPCR efficiency?

qPCR efficiency (often called “PCR efficiency”) describes how much the target amount increases per cycle. If your assay is perfectly efficient, the target doubles every cycle: an amplification factor $A = 2$ and an efficiency of $100\%$ .

Amplification factor

The calculator uses $A$ as “how many times the target multiplies per cycle”. A value near $2$ is the theoretical upper bound for a clean doubling reaction.

Efficiency (decimal)

Efficiency in decimal form is $E = A - 1$ . So $A=2$ corresponds to $E=1$ .

Efficiency (percent)

The percent form is $E_{\%} = 100\,E$ . Most people report this as a percent on reports and QC dashboards.

A practical rule of thumb: values around $90\%\text{ to }110\%$ are commonly considered acceptable for many assays, but your lab may set tighter QC limits depending on chemistry, platform, and validation.

In a standard-curve experiment, you typically plot cycle threshold against the log of input quantity. The slope of that line is the key input used to estimate efficiency.

The calculator supports two conventions (the “Standard” vs “Inverted” tabs). The math is the same; only which variable is on which axis changes how the slope is written.

How to calculate qPCR efficiency — Formula

The calculator is built around a simple relationship between slope, amplification factor, and efficiency. The most important idea is that once you know the slope of the standard curve, you can compute the per-cycle amplification.

Standard mode

If the plot is Cq vs $\log_{10}(\mathrm{Qty})$ , the common formula is:

A = 10^{-1/\text{slope}}

Then convert to percent efficiency:

E_{\%} = 100\,(A - 1)

Inverted mode

If the plot is $\log_{10}(\mathrm{Qty})$ vs Cq, the slope expression is:

A = 10^{-\text{slope}}

And again:

E_{\%} = 100\,(A - 1)

A quick sanity check

A perfect doubling reaction has $A = 2$ . In Standard mode, that corresponds to a slope near $-\tfrac{1}{\log_{10}(2)} \approx -3.322$ . In Inverted mode, it corresponds to $-\log_{10}(2) \approx -0.301$ .

✓Variables used

Slope

$\text{slope}$

Your standard curve's slope (from linear regression)

Amplification Factor

$A$

Per-cycle amplification (ideally ≈ 2)

Efficiency (Percent)

$E_{\%}$

Efficiency as a percentage (≈ 100%)

How to use the qPCR efficiency calculator — Example

You can type into any field (slope, amplification factor, or efficiency) and the calculator will solve the other two instantly. Here’s a typical “standard curve slope → efficiency” workflow.

Quick start (standard curve slope)

Choose the tab that matches your plot axes (Standard is the most common).
Paste your fitted slope from the standard curve regression.
Read the computed amplification factor and efficiency percent.
If the calculator shows a warning, treat it as a cue to review your dilution prep and assay setup.

Worked example

Suppose your regression slope is $\text{slope}=-3.35$ in Standard mode.

A = 10^{-1/\text{slope}}

=

10^{-1/(-3.35)}

=

10^{0.2985}

\approx

1.9884

E_{\%} = 100\,(A-1)

=

100\,(1.9884-1)

=

98.84\%

Interpretation: an efficiency around $98.84\%$ is typically considered solid, assuming the standard curve fit is clean and the dilution points are prepared accurately.

Real-world use cases

Comparing primer sets for the same target gene.
Checking whether a new master mix behaves like the old one.
Spotting dilution-series issues (pipetting, mixing, or contamination).
Documenting assay QC during validation or method transfer.

Helpful companion calculators

If you’re preparing serial dilutions, our Cell Dilution Calculator can help plan volumes quickly. And if you need a fast log conversion during analysis, try our Log Calculator.

How to optimize PCR efficiency and dilution curves

If your efficiency is consistently outside your target range, don’t panic. The number is sensitive to how the dilution series is prepared and how clean the regression fit is. The goal is to improve the experiment so the slope reflects true amplification, not prep artifacts.

!Common scenarios (and what they often mean)

🔴 Efficiency too low

Possible causes: inhibitors, suboptimal annealing, poor primer design, or under-mixing dilutions.

🟡 Efficiency too high

Possible causes: contamination, pipetting error across dilution points, non-linear region in the fit, or fluorescence thresholding issues.

🟠 Efficiency varies run-to-run

Possible causes: inconsistent template prep, evaporation, pipette calibration drift, or plate layout effects.

✨Tips & best practices

📊 Standard curve setup

• Use at least 5 dilution points
• 10-fold dilution series is common
• Run triplicates per point

🔍 Data quality

• Re-run if outliers appear
• Aim for $R^2 \ge 0.99$
• Exclude non-linear points

🧪 Lab technique

• Use clean, sterile workspace
• Include no-template control (NTC)
• Verify DNA template purity

⚙️ Optimization

• Change 1 parameter at a time
• Adjust primer/probe conc.
• Test annealing temp & Mg $^{2+}$

Example plate layout for a dilution series

Below is a simple template for placing a dilution series across a plate with replicates. Adjust to your lab’s workflow and the number of points you need.

Plate / Row	1	2	3	4	5	6
A	1	1	1	1
B	0.1	0.1	0.1	0.5	0.5	0.5
C	0.01	0.01	0.01	0.25	0.25	0.25
D	0.001	0.001	0.001	0.125	0.125	0.125
E	0.0001	0.0001	0.0001	0.0625	0.0625	0.0625
F	0.00001	0.00001	0.00001	0.03125	0.03125	0.03125
G	0.000001	0.000001	0.000001	0.015625	0.015625	0.015625
H	NTC	NTC	NTC	NTC	NTC	NTC

NTC means “no template control” — typically water or buffer, used to detect contamination or non-specific amplification.

FAQs

How do you calculate amplification efficiency for qPCR?

In Standard mode, compute $A = 10^{-1/\text{slope}}$ and then $E_{\%} = 100\,(A-1)$ . For example, with $\text{slope}=-3.35$ , you get $A\approx 1.9884$ and $E_{\%}\approx 98.84\%$ .

What is a good qPCR efficiency?

A common target is around $100\%$ . Many protocols consider something like $90\%\text{ to }110\%$ acceptable for a standard curve, but always follow your lab’s validation criteria.

Why can qPCR efficiency appear greater than 100%?

The calculation is based on a regression slope, so it can produce theoretical values above $100\%$ . That often points to issues like contamination, pipetting drift across dilutions, including non-linear points in the fit, or thresholding artifacts.

How do I get the slope from efficiency?

Convert percent to a factor: $A = 1 + E_{\%}/100$ . Then in Standard mode you can compute:

\text{slope} = -\frac{1}{\log_{10}(A)}

In Inverted mode the relationship is:

\text{slope} = -\log_{10}(A)

Does Ct (Cq) spacing relate to efficiency?

Yes. For a 10-fold dilution series, a perfectly efficient assay typically shows a Ct spacing near $3.322$ cycles between points. If you see consistently larger spacing, it often indicates lower amplification per cycle.

Limitations / disclaimers

This calculator estimates efficiency from an idealized standard-curve model.
It does not diagnose the root cause of poor performance (that requires experimental review).
Results should not replace your lab’s SOPs, validation plan, or platform-specific QC guidelines.

External references / sources

Bustin SA, et al. (2009). The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments.
Bio-Rad Laboratories. Real-time PCR applications guide (general efficiency and standard curve concepts).
Applied Biosystems / Thermo Fisher documentation on standard curves and efficiency interpretation (platform-specific nuances).

Note: references are provided for further reading; different chemistries and instruments may recommend slightly different acceptance thresholds.

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