Delta Delta Ct Calculator

Figran

Use the delta delta Ct calculator to turn Ct values into fold changes, a step-by-step table and a bar graph.

  • Livak 2−ΔΔCt or Pfaffl
  • Efficiency from a standard curve
  • Free SVG and 300 DPI PNG
Brackets
c-Mycc-Myc0246Relative expression(2−ΔΔCt)brainkidney

Group summary

Relative expression of c-Myc versus brain, normalized to GAPDH, calculated with the ΔΔCt method (Livak & Schmittgen 2001). Bars show fold changes from mean normalized log2 expression. Error bars show the range from ± SD on the log2 scale. Control uncertainty is not propagated. Sample sizes: brain, c-Myc: n = 6; kidney, c-Myc: n = 6.

GroupGenen (target / reference)Mean target CtMean reference CtMean ΔCtSD (log2)ΔΔCtMean log2 fold changeFold changeLowerUpper
brainc-Myc630.48523.6256.8600.1740.0000.0001.0000.8861.128
kidneyc-Myc627.02522.6604.3650.095−2.4952.4955.6375.2766.023

Individual fold-change points are not shown for separate wells because the measurements are not paired.

Step table

Target and reference wells are summarized independently for each group.

GroupGeneMean target CtMean reference CtMean ΔCtΔΔCtMean log2 fold changeFold change
brainc-Myc30.48523.6256.8600.0000.0001.000
kidneyc-Myc27.02522.6604.365−2.4952.4955.637

Delta delta Ct examples

Explore delta delta Ct examples for relative expression and primer efficiency.

Relative expression graph0246Relative expression(2−ΔΔCt)brainkidney

c-Myc in kidney vs brain

Compare kidney and brain using separate c-Myc and GAPDH wells.

Source: ABI User Bulletin #2; R pcr package (ct1)

Relative expression graph02.557.5Relative expression(2−ΔΔCt)brainkidney

Target and reference in the same well

Calculate paired variation when target and reference are measured in the same sample.

Source: ABI User Bulletin #2; R pcr package (ct2)

qPCR standard curve22.52527.53032.50.010.0320.10.321Quantity (log scale)Ctc-Myc y = −3.39x + 25.70R² = 0.997 · E = 97.3%GAPDH y = −3.41x + 22.68R² = 0.999 · E = 96.3%

Primer efficiency from a standard curve

Fit primer efficiencies to a seven-point dilution series using replicates reconstructed from published means and SD.

Source: R pcr package (ct3)

Relative expression graph0246Relative expression(efficiency-corrected)brainkidney

Efficiency-corrected fold change (Pfaffl)

Apply the measured primer efficiencies to the kidney and brain comparison.

Source: ABI User Bulletin #2; R pcr package (ct1 and ct3)

Relative expression graph01234Relative expression(2−ΔΔCt)target1target2controlrecoverytreatment

Control vs treatment

Compare treatment and recovery groups against a control.

3 groups · 9 samples · 2 targets

Relative expression graph0123log2 fold changetarget1target2controlrecoverytreatment

Instrument export with two reference genes, log2 fold change

Explore log2 fold change from an instrument export with two reference genes.

3 groups · 2 target genes · 2 reference genes

How to calculate delta delta Ct

Calculate relative gene expression from Ct values in four steps.

  1. 1Paste Ct values

    Enter an instrument export or a table of Ct values for the delta delta Ct calculation.

  2. 2Pick genes

    Select reference and target genes and a control group.

  3. 3Choose a method

    Select Livak or Pfaffl and an error-bar definition.

  4. 4Download

    Save the graph and tables or copy the legend.

The 2−ΔΔCt method step by step

The delta delta Ct method (also called ddCt or the Livak method) compares expression after normalizing to a reference gene and calibrating to a control group.

ΔCt (delta Ct) = Cttarget − Ctreference

ΔΔCt = ΔCtsample − mean ΔCtcontrol

Fold change = 2−ΔΔCt

GroupMean ΔCtΔΔCtFold change
brain6.8600.0001.000
kidney4.365−2.4955.637

Source: Livak and Schmittgen (2001).

Replicates and error bars

For delta delta Ct analysis, average technical replicates before calculating biological variation. A range on the Ct scale becomes asymmetric after conversion to fold change. MIQE guidelines (2009)

More than one reference gene

Normalize to the geometric mean of the reference genes’ relative quantities. Select validated reference genes for the experiment. Vandesompele et al. (2002)

qPCR efficiency and the Pfaffl method

A qPCR standard curve relates Ct to the logarithm of the input quantity. Use its slope to estimate primer efficiency:

E = 10−1/slope · Efficiency (%) = (E − 1) × 100

qPCR standard curve22.52527.53032.50.010.0320.10.321Quantity (log scale)Ctc-Myc y = −3.39x + 25.70R² = 0.997 · E = 97.3%GAPDH y = −3.41x + 22.68R² = 0.999 · E = 96.3%
Source: R pcr package (ct3); replicates reconstructed from published means and SD.

The Pfaffl method uses a separate efficiency for the target and reference. It treats the efficiencies as fixed in this calculator. Pfaffl (2001)

Ratio = EtargetΔCt(target) / EreferenceΔCt(reference)

Delta delta Ct FAQ

What is the delta delta Ct method?

The delta delta Ct method compares gene expression between a sample and a control after normalization to a reference gene. Calculate ΔCt, subtract the control ΔCt, and convert to fold change with 2−ΔΔCt.

What is the difference between ΔCt and ΔΔCt (delta Ct vs delta delta Ct)?

ΔCt normalizes a target to a reference gene; ΔΔCt also subtracts the control group’s ΔCt. The value 2−ΔCt is a relative expression measure within a sample.

How do I calculate fold change from Ct values?

For qPCR fold change, calculate 2−ΔΔCt. Values above 1 indicate higher expression, values below 1 indicate lower expression, and log2 fold change is −ΔΔCt.

When should I use the Pfaffl method instead of the ΔΔCt method?

Use efficiency correction when the target and reference efficiencies differ or depart from doubling. Estimate each efficiency from an appropriate standard curve.

How do I calculate qPCR efficiency from a standard curve?

Fit Ct against log10 quantity and calculate E = 10−1/slope. A slope of about −3.32 corresponds to E = 2, or 100% efficiency.

Why are the error bars on my fold change asymmetric?

A symmetric interval on the Ct scale becomes asymmetric after the exponential transformation. The control group’s uncertainty is not propagated into the other groups in the Livak range method.

Should I average technical replicates first?

Yes. Average technical wells for each biological sample and gene before calculating variation across biological samples. A technical SD above 0.5 cycles is flagged for review; check pipetting or remeasure. The calculator does not automatically remove wells.

How should I handle “Undetermined” Ct values?

Treat them as missing rather than replacing them with 0 or 40. This calculator excludes and lists them; their experimental meaning depends on the assay.

Is my data uploaded? What can I download?

Your data stays in your browser. Download SVG, 300 DPI PNG and CSV tables, or copy the figure legend without signing in.

Calculate your fold change

Turn Ct values into a relative expression graph.