Compute relative gene expression using the 2^-ΔΔCt method. Import RDML files or paste Ct values. Efficiency correction, outlier detection, and MIQE checklist. Data never leaves your browser.
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GAPDH and ACTB are popular but not universally stable. Both change expression in hypoxia, diabetes models, and many cancer contexts. Run a stability analysis (geNorm M < 0.5) before committing to a reference gene.
At high Ct values, SYBR Green signal from primer-dimers can be confused with true amplification. Always verify late Ct values with melt curve analysis. Consider using probes (TaqMan) for low-abundance targets.
Fold change is intuitive (2× upregulation) but misleading for downregulation (0.5× vs. −2×). Log2 fold change is symmetric: +1 = 2-fold up, −1 = 2-fold down. Use log2 FC for statistics and bar charts.
Three technical replicates from one sample tell you about pipetting precision, not biology. At minimum, use 3 biological replicates per group. Technical triplicates reduce noise but do not address biological variability.
Livak & Schmittgen (2001) 2^-ΔΔCt method with optional Pfaffl (2001) efficiency correction. Outlier detection via IQR method. MIQE checklist based on Bustin et al. (2009).
Last validated 2026-04-05. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.
ConductScience qPCR ΔΔCt Calculator (v1.0). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/qpcr-ddct-calculator
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2^−ΔΔCT method. Methods. 2001;25(4):402-408. doi:10.1006/meth.2001.1262
Bustin SA, et al. The MIQE guidelines. Clin Chem. 2009;55(4):611-622. doi:10.1373/clinchem.2008.112797
The ΔΔCt method normalizes gene expression in two steps:
1. ΔCt = Ct(target gene) − Ct(reference gene) — normalizes for RNA input 2. ΔΔCt = ΔCt(treatment) − mean(ΔCt(control)) — normalizes to baseline 3. Fold Change = 2^(−ΔΔCt) — converts to linear scale
The method assumes equal amplification efficiency (~100%) for all genes. When this assumption is violated, use the Pfaffl efficiency-corrected method.
The MIQE guidelines (Bustin et al., 2009) define the minimum information needed for reviewers to assess qPCR experiments. Key requirements:
• RNA quality: Report RIN values, A260/280, A260/230 • Primer validation: Show specificity (melt curve) and efficiency (standard curve) • Reference genes: Validate stability across conditions • Analysis: State quantification method and software used
The interactive MIQE checklist in this tool helps you document compliance systematically.
