Spot Colocalization
This tutorial demonstrates how to detect spots in two fluorescence channels and identify colocalising spot pairs — objects from both channels that overlap in the same spatial location.
Prerequisites
- Multi-channel images with spots in at least two distinct channels (e.g. Cy5 and Cy7).
Step 1: Define Classes
| Class | Purpose |
|---|---|
cy5@spot | Spots in channel 1 |
cy7@spot | Spots in channel 2 |
coloc@cy5cy7 | Colocalisation overlap area |
Step 2: Per-Channel Detection Pipelines
Create one pipeline per channel following the Spot Count workflow. Each pipeline should end with a Classify ROIs step that assigns the respective class:
- Pipeline 1 →
cy5@spot - Pipeline 2 →
cy7@spot
Step 3: Colocalization Pipeline
Create a third pipeline with Empty input (no image channel needed). Add a single step:
| Setting | Value |
|---|---|
| Classes to colocalize | cy5@spot, cy7@spot |
| Class for overlapping areas | coloc@cy5cy7 |
| Min colocalization area | 1 px² |
| Allow multi-object colocalization | disabled (one-to-one matching) |
Step 4: Run and Inspect
After running:
cy5@spotobjects that colocalize are assigned a tracking ID shared with their matchingcy7@spotpartner.- In the results table, sort by Tracking ID to see matched pairs side by side.
- The
coloc@cy5cy7class contains one object per colocalising pair, representing the overlap area.
Interpreting Results
| Metric | Meaning |
|---|---|
cy5@spot Count | Total Cy5 spots detected |
cy7@spot Count | Total Cy7 spots detected |
coloc@cy5cy7 Count | Number of colocalising spot pairs |
| Colocalisation % | coloc count / cy5 count × 100 (compute in export) |
Filtering by colocalization area
Add a Classify ROIs step after Colocalization targeting coloc@cy5cy7 to filter out low-overlap events:
| Filter | Value |
|---|---|
| Min area | 5 px² (discard single-pixel overlaps due to border artefacts) |