How to perform conditional cell classification

This guide shows you how classify cells from their features using conditional expressions.

Prerequisite: You have accurately segmented and measured a cell population.

Reference keys: characteristic group, phenotype

  1. Open an experiment project. In the header part, select the wells and positions you want to classify.

  2. Expand the block associated with your cell population of interest. Click on the triple dots icon in the MEASURE section to launch the classifier utility.

  3. Name the classification to create. For dynamic data this becomes the name of the event. For static data, it is the name of the group.

  4. Select two features that can clusterize the cells (e.g. area and adhesion channel intensity in a spreading classification).

  1. Explore Your Data:

    • Use the Frame Slider at the bottom to visualize the population feature distribution frame by frame.

    • Click the Project Times button to superimpose all timepoints on the same plot (useful for checking overall population clusters).

    • Use the Log Scale buttons next to each feature selector to switch between linear and log scales.

    • Adjust the Transparency Slider (bottom right) if points are too dense.

  2. Define the Class:

    Type a condition in the classify field. The syntax supports numeric comparisons, logic operators, and string matching.

    • Numeric conditions: area > 500, intensity < 200

    • Combinations: area > 500 and intensity < 200, area > 500 or circularity > 0.8

    • String/Category matching: well == "W1", label != "A" (use quotes for strings)

    • Complex columns: Use backticks for columns with special characters: `d/dt.area` > 0

  3. Preview:

    Press the Preview button.

    • Red points: Cells matching your condition (Positive).

    • Blue points: Cells not matching (Negative).

    Tip: Change the x/y features to verify that your classification makes sense in other dimensions.

  4. Apply (Static vs. Time-Correlated):

    • Static Group (Default): If Time correlated is unchecked, clicking Apply creates a standard group or status column. This is a frame-by-frame classification.

    • Time Correlated Event (For Tracked Data): If your data is tracked (contains TRACK_ID), you can check Time correlated. This fits a sigmoid to the binary signal of each track to detect when an event happens (e.g., cell death, specific state entry).

      Select the event type:

      • Unique state: The cell enters a state and stays there (or doesn’t).

      • Irreversible event: A definitive transition (like death).

      • Transient event: A state that can be entered and exited (e.g., calcium pulse).

      Note: The **R2 tolerance* slider defines how well the sigmoid must fit the data to accept the event time.*

  5. Press Apply to finalize. A new column (e.g., status_my_class) and potentially event times (t_my_class) will be added to your data.