LabTools

Molecular Genetics

qPCR Data Analysis: Efficiency, Reference Genes and ΔΔCq

This guide walks through analysing qPCR data: building a standard curve, checking amplification efficiency, choosing reference genes, and quantifying with the ΔΔCq method. Use the efficiency calculator built into the page as you go.

1. The standard curve and efficiency

Run a dilution series of a known template and plot Cq against log(dilution). The slope tells you the amplification efficiency — aim for 90–110% with R² > 0.98. Convert your slope here:

Efficiency = 10(−1/slope) − 1. Ideal slope −3.32 → 100% (doubling each cycle). Acceptable ~90–110% (slope −3.6 to −3.1). Slope comes from a Cq-vs-log(dilution) standard curve.

A slope of −3.32 is exactly 100% (the template doubles each cycle). See the dedicated slope-to-efficiency page for troubleshooting.

2. Cq (Ct) and what it means

The quantification cycle (Cq, formerly Ct) is the cycle at which fluorescence crosses the threshold. Lower Cq = more starting template. Always set the threshold consistently across a run, and inspect the melt curve to confirm a single specific product.

3. Choose and validate reference genes

Relative quantification normalises your target to one or more stable reference genes. Don’t assume a “housekeeping” gene is stable in your system — validate candidates and rank them with a tool such as BestKeeper. Using two or more validated references is best practice.

4. Relative quantification (ΔΔCq)

For assays with similar, near-100% efficiencies, the comparative method applies:

If efficiencies differ from 100% or from each other, use an efficiency-corrected model (e.g. Pfaffl) instead of 2−ΔΔCq.

5. Controls and reporting

Frequently asked questions

What efficiency is acceptable for ΔΔCq?

Target and reference assays should be 90–110% efficient and similar to each other; otherwise use an efficiency-corrected model.

How many reference genes should I use?

At least two validated, stably expressed genes; rank candidates with a tool like BestKeeper.

What is the difference between Cq and Ct?

They are the same value — Cq (quantification cycle) is the MIQE-recommended term for what was called Ct (threshold cycle).