Melt Curve Peak Tm Identifier Calculator

Example data table

Formula used

• Smoothing (moving average): each point becomes the mean of a neighboring window.
• Derivative: central difference dF/dT ≈ (Fᵢ₊₁ − Fᵢ₋₁) / (Tᵢ₊₁ − Tᵢ₋₁) or forward difference (Fᵢ₊₁ − Fᵢ) / (Tᵢ₊₁ − Tᵢ).
• Peak trace: commonly −dF/dT to show melt transitions as positive peaks.
• Auto thresholds: computed from the peak-trace standard deviation (Height ≈ 2×SD, Prominence ≈ 1.5×SD).
• Primary Tm: selected by the chosen strategy (highest peak, or nearest expected Tm).

How to use this calculator

1. Paste data or upload a CSV file.
2. Select units and optional analysis range.
3. Adjust smoothing and thresholds if needed.
4. Choose a primary peak selection strategy.
5. Press Submit to view results and exports.

Melt curve peak calling focuses on transition kinetics

Melt curves summarize how double stranded products dissociate as temperature rises. The calculator converts fluorescence readings into a peak trace so transition midpoints become measurable. A clear peak typically indicates a dominant amplicon, while multiple peaks can signal mixed products or primer dimers. Use the peak list to document each domain and compare runs.

Smoothing and step size control noise in derivatives

Derivative curves amplify measurement noise, especially when temperature increments are small or fluorescence is unstable. The moving average window reduces high frequency fluctuations before differentiation. If the median temperature step exceeds about 1.5°C, peaks may broaden and shift. If the step is very small, stronger smoothing often improves peak stability.

Thresholds use height and prominence to filter artifacts

Peak height reflects transition strength, while prominence estimates separation from surrounding baseline. Auto thresholds are derived from the standard deviation of the peak trace, giving adaptive filtering across assays. Manual values help when you know expected signal strength. A larger prominence window is useful for broad transitions, while a smaller window helps resolve close shoulders.

Primary Tm selection supports expected target validation

When multiple peaks pass filters, primary Tm can be selected by maximum height or by proximity to an expected Tm. The expected option is helpful for genotyping panels, HRM screening, or assays with known controls. The confidence metric (height divided by trace SD) summarizes how strongly the primary peak stands above noise.

Exports improve traceability and audit readiness

The full series export includes temperature, raw fluorescence, smoothed fluorescence, and the peak trace used for calling. The peaks only export provides a concise table for LIMS entry and batch review. PDF reports are useful for approvals and attachments. Store the chosen settings alongside results to reproduce calls consistently across instruments and operators.

FAQs

1) What does Tm represent in this tool?
It reports the temperature at the maximum peak in the derivative based trace, which corresponds to the midpoint of the main melt transition for the selected peak.

2) Why do I see multiple peaks?
Multiple peaks may indicate mixed amplicons, nonspecific products, heteroduplexes, or primer dimers. Tighten assay conditions, adjust thresholds, or select the peak nearest to an expected target.

3) Should I use −dF/dT or dF/dT?
Most assays show decreasing fluorescence as temperature increases, so −dF/dT produces positive peaks. If your signal increases with temperature, use dF/dT instead.

4) How do I choose the smoothing window?
Start with 5 to 9 points. Increase it if the trace is jagged, and decrease it if true peaks look flattened or shifted. Keep an odd value for symmetry.

5) What do height and prominence mean?
Height measures peak amplitude, while prominence measures how distinctly the peak rises above its local baseline. Prominence is better for rejecting shoulders and noise driven spikes.

6) Why does the primary peak change after filtering?
Filtering can remove small peaks or merge close peaks when minimum distance is high. Review detected peaks and settings, then use the expected Tm strategy if a target peak is known.