📈 qPCR Efficiency Calculator
Convert the slope of a qPCR standard curve into amplification efficiency, and see the fold change per cycle.
Amplification efficiency
E = 10^(−1/slope) − 1
100.1%
Fold change per cycle
ideal is 2× (slope −3.32, 100%)
2.001×
How the qpcr efficiency calculator works
From a standard curve of Cq versus log(template), the amplification efficiency is E = 10^(−1/slope) − 1. A perfect reaction doubles the product each cycle, which corresponds to a slope of −3.322 and 100% efficiency. Acceptable assays generally fall in the 90–110% range (slope roughly −3.6 to −3.1).
A fixed formula from the standard curve — no reference data. Enter the slope your qPCR software reports (it is negative) to get the efficiency and per-cycle fold change.
Frequently asked questions
How do you calculate qPCR efficiency from the slope?
Efficiency E = 10^(−1/slope) − 1, expressed as a percentage. A slope of −3.32 gives 10^(1/3.32) − 1 = 2 − 1 = 1.00, i.e. 100% efficiency (the product doubles each cycle).
What slope means 100% efficiency?
−3.322. That is the slope at which each cycle exactly doubles the amount of product, which is the definition of 100% amplification efficiency.
What is an acceptable qPCR efficiency?
Generally 90–110%, corresponding to a standard-curve slope of about −3.6 to −3.1. Outside that range suggests inhibitors, pipetting error, poor primer design or a suboptimal standard curve.
What does the fold change per cycle mean?
It is 10^(−1/slope) — how much the target amplifies each cycle. Ideal is 2× (doubling). A value below 2 means less than perfect efficiency; the reaction amplifies more slowly than doubling.
Why is the slope negative?
Because Cq (the cycle at which signal crosses threshold) decreases as template concentration increases — more starting template crosses threshold sooner. Plotting Cq against log(template) therefore gives a negative slope.
What is R² and why does it matter here?
R² measures how well the standard-curve points fit a straight line (aim for ≥ 0.98). This tool computes efficiency from the slope; a good R² is what makes that slope — and the efficiency — trustworthy.