What you need
Ct values for a target gene and a reference gene (a housekeeping gene such as GAPDH or ACTB whose expression does not change with the treatment), measured in a treated sample and a control sample.
The three steps
- Normalize each sample to the reference gene: ΔCt = Ct target − Ct reference.
- Compare treated with control: ΔΔCt = ΔCt treated − ΔCt control.
- Convert to fold change: fold change = 2−ΔΔCt.
A worked example
Treated: target Ct 22.1, reference Ct 18.0, so ΔCt = 4.1. Control: target Ct 24.5, reference Ct 18.0, so ΔCt = 6.5.
ΔΔCt = 4.1 − 6.5 = −2.4, and fold change = 22.4 = 5.3. The target is expressed about 5.3 times more in the treated sample. A fold change below 1 means lower expression; 0.5 is half.
When 2^-ΔΔCt is not enough
The method assumes both primer pairs are close to 100% efficient, doubling the product every cycle. Check this with a standard curve; 90% to 110% is the usual range. If the efficiencies differ, use the Pfaffl method, which puts each gene's own efficiency into the calculation: ratio = EtargetΔCt target ÷ EreferenceΔCt reference, where each ΔCt is control minus treated and E = 1 + efficiency.
Replicates and statistics
- Average technical replicates (wells of the same sample) before working out ΔCt.
- Run statistics on the ΔCt or ΔΔCt values of biological replicates, not on the fold changes, because fold change is not normally distributed.
- Report the log2 fold change, which is simply −ΔΔCt, when you want up- and down-regulation on the same scale.
Calculator
The ΔΔCt Calculator averages replicate Ct values, gives ΔCt, ΔΔCt, fold change and log2 fold change, and switches to the Pfaffl method when you enter primer efficiencies. For absolute quantification with a standard curve, the DNA Copy Number Calculator works out the copies in each standard.