qPCR Calculator
A free online qPCR calculator implementing the ΔΔCt (Livak) method for relative gene expression analysis. Enter Ct values for target and reference genes across samples, visualize fold changes with error bars, check PCR efficiency from standard curve dilutions, and export results as CSV — all processed in your browser with no data uploaded.
| Sample Name | Target Gene Ct | Reference Gene Ct | Control | |
|---|---|---|---|---|
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What is a qPCR Calculator?
A qPCR (quantitative PCR) calculator analyzes real-time PCR data to determine relative gene expression levels between samples. The ΔΔCt method (Livak method) compares threshold cycle (Ct) values of a target gene normalized to a reference housekeeping gene, then calculates fold change relative to a control sample. This is the standard approach for measuring how much a gene is up- or down-regulated in an experimental condition.
How to Use This Calculator
- Add samples with their Ct values for target and reference (housekeeping) genes
- Mark at least one sample as the control (calibrator)
- Click Analyze to calculate ΔCt, ΔΔCt, and fold change for each sample
- View the fold change bar chart comparing expression levels
- Optionally check PCR efficiency from standard curve data in the Efficiency tab
- Export results as CSV for further analysis in Excel or R
Frequently Asked Questions
What is the ΔΔCt method?
The ΔΔCt (delta-delta-Ct) method calculates relative gene expression in two steps: (1) ΔCt = Ct(target) - Ct(reference) normalizes to a housekeeping gene, (2) ΔΔCt = ΔCt(sample) - ΔCt(control) normalizes to a control sample. Fold change = 2^(-ΔΔCt). This assumes ~100% PCR efficiency.
What PCR efficiency is acceptable?
Ideal PCR efficiency is 100% (doubling per cycle). Acceptable range is 90-110% (efficiency 0.9-1.1). Efficiency is calculated from the slope of a standard curve: E = 10^(-1/slope) - 1. A slope of -3.322 indicates 100% efficiency.
When should I use the Pfaffl method instead of Livak?
Use the Pfaffl method when PCR efficiencies of your target and reference genes differ significantly (more than 5%). The Pfaffl method incorporates individual gene efficiencies: Ratio = (E_target)^ΔCt(target) / (E_ref)^ΔCt(ref). The Livak method assumes both genes have ~100% efficiency.