Protein Tab

The Protein Tab estimates the size and shape of a translocating protein from its nanopore blockage signal. Given the pore’s diameter and length, it fits a two-population (prolate/oblate) volume-and-shape-factor model to either a single event at a time (Individual mode) or the aggregate distribution across many events (Ensemble mode), using Monte Carlo rejection sampling to recover the most likely volume and shape factor for each population.

Step 1: Load a Fitted Events Database

  1. Click the ➕ button to load a database of fitted events (the output of the EventAnalysis tab’s Commit).

  2. A plugin dialog (e.g., SQLiteDBLoader) will appear. Enter a custom Name for the loader instance and select the SQLite .db file to load.

Step 2: Choose Scope

Click the Scope button to select which experiments and channels contribute to the current plot. By default, everything is selected.

Step 3: Enter Pore Geometry

Enter the pore diameter and pore length, in nanometers, in their respective fields. Both are required for the volume/shape-factor fit; without them, the physical model has no way to convert a blockage fraction into a volume.

Step 4: Choose a Fitting Mode

Select Individual to fit each event separately, or Ensemble to fit one shared volume/shape-factor distribution across every event currently in scope.

Note

Individual and Ensemble modes keep fully independent plots and fit state. Switching modes shows that mode’s own last-drawn plot immediately, with no need to re-run Update Plot, and never overwrites the other mode’s results.

Step 5: Configure Sampling and Binning

  1. Set N, the number of Monte Carlo samples used to estimate volume and shape factor for each population.

  2. Specify the histogram bins as a count (e.g., 50), or check Sizes to specify bin widths instead.

Step 6: Generate the Fit

Click Update Plot to run the fit for the current mode. This draws:

  • A ΔI/I (or volume) histogram, or a Peak Scatterplot in Individual mode.

  • The Prolate/Oblate volume vs. shape-factor solutions on the second plot.

Step 7a: Commit Individual Fits

In Individual mode, once a fit has been generated, click Commit Individual to write the per-event fit results to the database. If the target columns already exist, you’ll be prompted before anything is overwritten.

Step 7b: Report Ensemble Fit

In Ensemble mode, click Report All to display the double-Gaussian fit parameters (peak amplitude, mean, standard deviation) for the current binning, along with median ± standard deviation summaries of Prolate and Oblate volume, a, b, and shape factor m from the Monte Carlo sample. Ensemble mode has no single event to write a database row against, so this is display-only.

Step 8: Apply Filters

You can restrict the events included in a fit to a named subset:

  1. Click the ➕ filter button to define a new filter, either against the full database or the currently selected experiments/channels.

  2. Use the filter dropdown to choose which saved subset(s) are active for the current plot.

  3. Click the info/edit button next to the dropdown to view or modify the currently selected subset.

  4. Click the delete button to remove selected subsets (individual ones can also be removed directly from the dropdown).

  5. Use Save Filter / Load Filter to persist subsets for future sessions.

Step 9: Export Plot Data

Click Export Plot Data to save the data currently shown in your plots to disk.

Step 10: Inspect Individual Events

  1. Use Scope to select exactly one experiment and channel.

  2. Enter a starting event ID and the number of events to visualize.

  3. Click Plot Events to view raw/filtered/fitted traces, or Plot Histogram for a ΔI/I histogram, for the selected events.

  4. Use the left/right arrow buttons to step through events in the filtered set.

  5. Check the RAW box to overlay the unfiltered raw signal alongside the filtered and fitted traces.