Exporting Mic qPCR Data to GraphPad Prism: What Actually Works

The Mic qPCR cycler from Bio Molecular Systems exports data as .csv or .xlsx files from its micPCR software, but the column layout doesn't match what Prism expects for grouped analyses or XY plots. To get your Ct values, melt curve data, or amplification curves into Prism cleanly, you need to restructure the exported table — either manually or with a copy-paste workflow that takes about two minutes once you know the layout Prism wants.

Here's the short version: export your results table from micPCR as a .csv, open it in Excel or Google Sheets, pivot your data so that each column represents a group (treatment, genotype, condition) and each row holds replicate Ct values, then paste that into a Prism Column analysis table. For amplification curves, you want an XY table where column A is cycle number (1–40) and subsequent columns are fluorescence values per well. The rest of this post walks through both scenarios with the specific column headers the Mic software gives you.

How the Mic Software Exports Data

The micPCR analysis software (current versions 2.x) gives you several export options under File → Export. The most useful ones:

• Results Table — one row per well, with columns for Well, Sample Name, Target, Ct (or Cq), and quantification data if you ran a standard curve. This is what you want for ΔΔCt analysis.
• Amplification Data — cycle-by-cycle fluorescence for every well. Columns are typically Cycle, then one column per well (labeled by well position like A1, A2, etc.).
• Melt Curve Data — temperature vs. −dF/dT, same column-per-well layout as amplification data.

The catch is that the Results Table comes in a "long" format — every well is a row, and if you have multiple targets (say GAPDH and your GOI), they're stacked vertically. Prism's Column analysis tables expect a "wide" format where each column is a dataset. The Amplification Data export is already in a Prism-friendly XY format, which is convenient.

One thing to watch: the Mic software sometimes includes header rows with run metadata (instrument serial number, run date, protocol name) above the actual data table in the .csv. Open the file and delete those rows before importing anywhere, or Prism will choke on them.

Reformatting Ct Values for Prism Column Analysis

Let's say you ran a ΔΔCt experiment with three groups (Control, Treatment A, Treatment B), three biological replicates each, and two targets (ACTB as reference, MYC as GOI). The Mic export gives you something like this:

What Prism wants for a grouped analysis (two-way layout, or even a simple column layout of ΔCt values) looks like this:

Where those values are ΔCt (GOI Ct minus reference Ct) for each replicate.

Steps to get there:

1. Open the .csv in Excel. Delete any metadata header rows so row 1 is the column headers.
2. Calculate ΔCt for each sample. If your Mic export has both targets in the same file, filter or sort by Target, then subtract: ΔCt = Ct(MYC) − Ct(ACTB) for each biological replicate. For the example above, Ctrl_1 ΔCt = 22.8 − 15.2 = 7.6.
3. Arrange ΔCt values into columns by group. You're building a small table where each column is a condition and each row is a replicate.
4. In Prism, create a Column analysis table (or Grouped if you have multiple GOIs). Paste your values directly.
5. Run your stats in Prism on the ΔCt values — unpaired t-test for two groups, one-way ANOVA for three or more. Then use Prism's transform to calculate fold change (2^−ΔΔCt) for plotting if you want a bar graph on a linear fold-change scale.

A common mistake: people calculate fold changes in Excel first, then paste those into Prism and run stats on them. Don't do this. Fold changes are on an exponential scale and are not normally distributed. Statistics should be performed on ΔCt values (Livak and Schmittgen, 2001). Prism can transform to fold change after the stats are done using Transform → User-defined → 2^(−Y) or you can set this up in the graph axis.

Getting Amplification Curves and Melt Data into Prism XY Plots

This is actually the easier case. The Mic's amplification data export is already structured as an XY table:

In Prism:

1. Create a new XY data table.
2. Set X to be cycle number (or let Prism auto-number rows).
3. Paste your fluorescence columns as Y datasets. You can rename the column headers from well positions (A1, A2) to meaningful sample names.
4. Plot as connected lines, no symbols — this gives you the classic amplification curve look.

For melt curves, the process is identical except X is temperature (typically 65–95°C in 0.5°C increments) and Y is −dF/dT. The Mic does the derivative calculation internally before export, so you're plotting the processed melt peak data.

Tip for cleaner melt curve plots: The Mic's default melt resolution is quite good (its rotating architecture gives even heating), but you'll sometimes see noisy derivative data at the temperature extremes. In Prism, you can trim the X range to 70–92°C to cut out the noisy tails and focus on the informative region. A single sharp peak at your expected Tm (typically 78–88°C for most amplicons with SYBR-based chemistry) is what you want. Shoulders or double peaks mean primer-dimer or off-target amplification — but that's a primer design problem, not a data export problem.

Handling the Mic's 4-Channel Multiplex Data

The Mic runs up to four channels (Green, Yellow, Orange, Red), and if you're doing multiplex TaqMan assays, the export file may contain fluorescence data from all channels interleaved or in separate sheets. When exporting from micPCR:

• Use Export → Results and filter by channel/target to get channel-specific Ct values.
• If exporting amplification data for all channels, you'll get separate cycle-vs-fluorescence tables per channel. Import each into its own Prism XY table or stack them as separate datasets within one table.

For a typical two-plex (say GAPDH-VIC and GOI-FAM), export each channel separately to avoid confusion. The Mic software lets you select which channels to include in the export — use this. Having a single file with 48 wells × 4 channels worth of fluorescence columns is unwieldy and easy to mis-paste.

Common Pitfalls When Moving Mic Data to Prism

Decimal separators. If your system locale uses commas as decimal separators, the .csv export from micPCR may use semicolons as field delimiters. Prism handles this fine if you import via File → Import, but copy-paste from Excel can scramble your values. Check that 15.2 didn't become 152.

Well numbering. The Mic is a 48-well rotor format, not a 96-well plate. Wells are numbered 1–48 (or labeled with a single letter-number scheme depending on your software version), not A1–H12. This doesn't affect analysis, but when you're labeling Prism columns, don't confuse your layout map.

Baseline correction. The micPCR software applies its own baseline subtraction and Ct determination algorithm. If you export raw fluorescence and try to re-determine Ct in another tool, you'll get different values. Stick with the Ct values from the Results Table export — those match what you see in the micPCR analysis window, and they're what you should report.

Replicate averaging. The Mic software can average technical replicates internally, but I'd recommend exporting individual well data and doing the averaging in Prism or during your ΔCt calculation. This lets you check replicate concordance (your technical replicates should be within 0.5 Ct of each other — if they're not, you have a pipetting problem) and Prism can display individual data points on your bar graphs, which reviewers increasingly expect to see.

A Faster Option

If you're running ΔΔCt analysis regularly and the export-reformat-paste workflow feels tedious, VoilaPCR accepts Mic qPCR export files directly and handles the ΔCt calculations, statistical tests, and fold-change plots without the Excel reformatting step. You can then export publication-ready figures or grab the processed data table for Prism if that's where you prefer to make your final graphs.