Molecular biology
qPCR analysis with the ΔΔCt method
From Ct values to fold change, and which numbers to use for statistics.
The calculation
- Average technical replicates for each sample and gene. Replicates more than about 0.5 cycles apart deserve a check.
- ΔCt = Ct(target) − Ct(reference). With several reference genes, use their mean Ct (equivalent to the geometric mean of their quantities).
- ΔΔCt = ΔCt(sample) − mean ΔCt(control group).
- Fold change = 2−ΔΔCt. The control group then averages about 1.
Assumptions
- Amplification efficiencies of target and reference genes are close to 100% (usually accepted as 90–110%) and similar to each other. If not, use an efficiency-corrected method.
- The reference genes do not change with your treatment. Check this; do not assume it.
- Melt curves show a single product, and no-template controls stay negative.
Which numbers go into the statistics?
Fold changes are on a multiplicative scale and are skewed. Run t-tests or ANOVA on the ΔCt (or −ΔΔCt) values, which are on a log scale, and present fold changes in the graph. The experimental unit is the animal or participant, not the well.
Report
Primer sequences, reference genes, efficiency, the number of biological and technical replicates, and the method. The MIQE guidelines give the full checklist.
References: Livak KJ, Schmittgen TD. Methods, 2001. Bustin SA, et al. The MIQE guidelines. Clinical Chemistry, 2009.
Published 2026 by Dr. Ambuj Shahi. This guide is general information for researchers; follow your institution’s and journal’s requirements.