How this instrument works
Quantitative PCR amplifies a target sequence exponentially, doubling in an ideal reaction with each thermal cycle, and a standard curve — a plot of the cycle threshold (Ct) against the log of starting template amount across a dilution series — measures how close a specific assay comes to that ideal. The curve's slope feeds directly into amplification efficiency through E = 10^(−1/slope) − 1, where E is expressed as a fraction (E = 1.0 means perfect 100% doubling each cycle) or, multiplied by 100, as a percentage.
The −1/slope inside that formula isn't arbitrary: at perfect 100% efficiency, template amount exactly doubles each cycle, so log10(2) = 0.30103 cycles of Ct shift correspond to each 10-fold dilution step — which means the mathematically exact ideal slope is −1/log10(2), or about −3.32. A measured slope close to −3.32 signals a reaction amplifying close to the theoretical doubling limit; a slope further from −3.32 in either direction signals a less efficient reaction.
In practice, assay validation typically treats efficiency between about 90% and 110% (roughly slopes between −3.10 and −3.58) as acceptable for reliable relative quantification, since low efficiency undercounts template at higher cycle numbers and inflated efficiency above 100% usually signals a technical problem — pipetting error in the dilution series, PCR inhibitors carried over from the sample, or primer-dimer formation — rather than a genuinely superior reaction, since no biochemical process legitimately exceeds one round of template doubling per cycle.
- Enter the slope from your Ct-versus-log-quantity standard curve into Standard-curve slope — it must be negative.
- Read Amplification efficiency (fraction) beneath it — 1.0 represents perfect 100% doubling per cycle.
- Read Amplification efficiency (%) for the same figure expressed as a percentage.
- A slope near −3.32 indicates near-ideal efficiency; slopes noticeably shallower or steeper than that indicate a less efficient assay worth investigating.
Worked example — standard-curve slope of -3.32
Enter -3.32 into Standard-curve slope. -1/-3.32 = 0.301205; 10^0.301205 works out to about 2.000806; subtracting 1 gives Amplification efficiency (fraction) = 1.00080525456, and Amplification efficiency (%) = 100.080525456%.
A slope of -3.32 is a commonly used practical reference point for a near-ideal qPCR assay, and the result confirms why: it computes to just barely above 100% efficiency, essentially indistinguishable from perfect cycle-by-cycle doubling once you account for normal rounding in how the reference slope itself is quoted.
Questions
What slope gives exactly 100.000% qPCR efficiency?
The mathematically exact slope for 100.000% efficiency is −1/log10(2), which works out to about −3.321928 — the value at which 10^(−1/slope) equals exactly 2, meaning the template truly doubles each cycle. In practice, −3.32 (a rounded version of that exact figure) is the commonly used reference slope for 'ideal' efficiency in qPCR literature and software.
What range of qPCR efficiency is considered acceptable?
Roughly 90% to 110% is the commonly cited acceptable range for a validated qPCR assay, corresponding to standard-curve slopes of roughly −3.10 to −3.58. Efficiency below 90% suggests inhibition or a suboptimal primer/probe design; efficiency noticeably above 110% usually points to a technical artifact in the standard curve, like pipetting error in serial dilutions, rather than a genuinely faster-than-ideal reaction.
Can amplification efficiency legitimately be over 100%?
Not biologically — no PCR reaction actually more than doubles its template in a single cycle, so a calculated efficiency noticeably above 100%, say above 110%, is a sign of a problem in how the standard curve was generated rather than a real superior reaction. Common causes include pipetting inaccuracy across serial dilutions, contamination, or PCR inhibitors present at different concentrations across the dilution series.
Why does a shallower slope, like -4, mean lower efficiency?
A shallower (less negative) slope means the Ct value shifts by fewer cycles for each 10-fold dilution step than the ideal −3.32 would predict, which happens when each cycle isn't quite doubling the template — the reaction needs more cycles to catch up to where a perfectly efficient one already would be. A slope of −4, for example, computes to about 77.8% efficiency, meaningfully below the ideal doubling rate.
How is the standard-curve slope itself calculated?
It comes from running a dilution series of known template quantity, plotting each dilution's Ct value against the log10 of its starting quantity, and fitting a straight line, typically by linear regression, through those points — the fitted line's slope is what gets entered into this calculator. That fitting step happens in your qPCR instrument's software or a spreadsheet, upstream of the efficiency calculation this instrument performs.