qPCR ΔΔCt Calculator

What is Ct (Cycle Threshold)?

In real-time PCR (qPCR), fluorescence increases as DNA is amplified. The Ct (cycle threshold)is the PCR cycle number at which the fluorescence signal crosses a defined threshold, indicating detectable amplification above background.

Lower Ct values indicate more abundant starting template (fewer cycles needed to reach threshold), while higher Ct values indicate less abundant template. A difference of 1 Ct cycle represents approximately a 2-fold difference in starting template (assuming 100% efficiency).

The ΔCt Calculation

ΔCt (delta Ct) normalizes target gene expression to a reference gene (also called a housekeeping or endogenous control gene). This corrects for differences in:

• Sample input amount
• RNA quality
• Reverse transcription efficiency
• Sample-to-sample variation

Common reference genes include GAPDH, β-actin, 18S rRNA, and HPRT, though the choice depends on the experimental context and must be validated for stability.

The ΔΔCt Calculation

ΔΔCt (delta-delta Ct) compares the normalized expression in a sample to a reference condition called the calibrator. The calibrator is typically:

• An untreated control sample
• A time-zero baseline
• A wild-type or normal tissue sample
• Any defined reference condition

The calibrator has a ΔΔCt of 0 and a fold change of 1.0 by definition.

Fold Change: 2^(−ΔΔCt)

The fold change represents relative expression compared to the calibrator:

Amplification Efficiency

The simple 2^(−ΔΔCt) method assumes 100% amplification efficiency for both target and reference genes—meaning the amount of PCR product exactly doubles with each cycle.

In practice, efficiency varies between 85–110%. Efficiency is typically determined from standard curves using:

When efficiencies differ significantly from 100% or between genes, an efficiency-adjusted calculation (similar to the Pfaffl method) provides more accurate relative quantification. When both efficiencies are close to 100%, the efficiency-adjusted result approximates the simple method.

Limitations of This Calculator

• No replicate averaging: Each Ct value is treated as a single point. Real analysis requires biological and technical replicates.
• No error propagation: Standard deviations and confidence intervals are not calculated.
• No statistical testing: Significance of fold changes must be determined with appropriate statistical methods.
• No quality control: Melt curves, amplification curves, and standard curves are not evaluated.
• Idealized assumptions: Does not account for primer dimers, inhibitors, or other PCR artifacts.