Basic Workflow

This guide covers the complete single-image analysis workflow with all options and parameters.

Workflow Overview

The basic workflow consists of seven main steps:

  1. Configure channel identifiers

  2. Load images

  3. Segment chromosomes (optional)

  4. Detect spots in both channels

  5. Find common regions

  6. Measure intensities

  7. Export results

Each step is detailed below with all available options.

Step 1: Channel Identifier Configuration

Before loading images, configure the channel identifiers to match your naming convention.

Channel identifier setup

Channel identifier configuration panel

Configuration Fields:

DAPI Channel Identifier

Enter the string that identifies DAPI images in your filenames.

  • Examples: 435, dapi, DAPI, w435

  • Used for: Chromosome segmentation

Channel 1 Identifier (DNA-FISH)

Enter the string that identifies DNA-FISH images.

  • Examples: 525, dna_fish, DNA-FISH, w525

  • Used for: Primary spot detection

Channel 2 Identifier (CENP-C)

Enter the string that identifies CENP-C images.

  • Examples: 679, cenpc, CENP-C, w679

  • Used for: Secondary spot detection

File Naming Examples:

Match these patterns:

``` # Numeric identifiers sample_001_w435.tif (DAPI) sample_001_w525.tif (DNA-FISH) sample_001_w679.tif (CENP-C)

# Descriptive identifiers cell_01_dapi.tif cell_01_dna_fish.tif cell_01_cenpc.tif

# Mixed format image_435_ch1.tif image_525_ch2.tif image_679_ch3.tif ```

Note

The identifier can appear anywhere in the filename. The software searches for the substring within each filename.

Step 2: Loading Images

Image loading

After loading images - folder list appears on the left

To Load Images:

  1. Click the Load Images button

  2. Navigate to your folder containing image files

  3. Click Select

What Happens:

  • Software searches for files matching your channel identifiers

  • Matching images are loaded into the napari viewer

  • Image sets appear in the folder list (left panel)

  • Click any folder in the list to switch between image sets

Skip Segmentation Option:

Tip

Check Skip Segmentation before loading if:

  • You don’t have DAPI images

  • You only want to analyze spot co-localization

  • Segmentation is not needed for your analysis

When checked, the software skips Step 3 and goes directly to spot detection.

Step 3: Chromosome Segmentation

Segmentation result

Segmentation output showing individual chromosomes with unique labels

To Segment:

Click Segment (DAPI) Image

Processing:

  • Uses trained Cellpose model for metaphase chromosomes

  • Automatically detects chromosome boundaries

  • Creates a labels layer with unique ID for each chromosome

  • Each chromosome is displayed in a different color

Segmentation Parameters:

The Cellpose model uses these default parameters:

  • Model: Custom trained for metaphase chromosomes

  • Diameter: Automatically determined

  • Channels: [0,0] for grayscale DAPI

  • GPU: Enabled if available

Post-processing Options:

Available through checkboxes (if implemented):

  • Remove small objects: Filters out noise

  • Remove edge objects: Excludes chromosomes touching borders

  • Fill holes: Fills gaps within chromosomes

  • Smooth boundaries: Applies morphological smoothing

Typical Processing Time:

  • With GPU: 5-15 seconds

  • Without GPU: 30-60 seconds

Step 4: Spot Detection

Detect spots in both channels using adjustable thresholds.

Adjusting Thresholds

Threshold sliders

Threshold adjustment controls

DNA-FISH Threshold Slider:

  • Range: 0-100

  • Default: 50

  • Lower values = more spots detected (more sensitive)

  • Higher values = fewer spots detected (more specific)

CENP-C Threshold Slider:

  • Same range and behavior as DNA-FISH

  • Independently adjustable

  • Optimize based on your image quality

Important

Changing the slider resets detection status. You must re-run detection after adjusting thresholds.

Detecting Channel 1 Spots

  1. Adjust the DNA-FISH Threshold slider

  2. Click Detect Channel 1 Spots

  3. Wait for processing to complete

Channel 1 detection

Channel 1 spots detected - shown as brown markers

What You’ll See:

  • New layer: “Channel 1 spots”

  • Colored markers at each detected spot location

  • Toggle the DNA-FISH layer to see overlay

Detecting Channel 2 Spots

  1. Adjust the CENP-C Threshold slider

  2. Click Detect Channel 2 Spots

  3. Wait for processing

Both channels detected

Both channels with detected spots

Optimization Tips:

  • Start with default value (50)

  • If too few spots: decrease threshold by 10

  • If too many false positives: increase threshold by 10

  • Test on a representative image before batch processing

Step 5: Finding Common Regions

Common regions

Finding common regions interface

Click Find Common to identify overlapping signals.

What This Does:

  • Identifies chromosomes (or regions) with both Channel 1 and Channel 2 spots

  • Creates a filtered dataset of co-localized signals

  • Removes background and non-overlapping signals

Why It’s Important:

  • Ensures meaningful co-localization

  • Reduces false positives

  • Improves quantification accuracy

Output:

  • New layer showing common regions

  • Only spots in common regions will be used for intensity measurements

Step 6: Measuring Intensities

Click Get Intensity at Spots Location

Measurements Performed:

  • Channel 2 intensity at each Channel 1 spot location

  • Channel 1 intensity at each Channel 2 spot location

  • Background-subtracted values

  • Spot coordinates

CSV Output Format:

The saved file contains columns:

  • spot_id: Unique identifier for each spot

  • x_coordinate: X position in pixels

  • y_coordinate: Y position in pixels

  • channel1_intensity: Intensity in Channel 1

  • channel2_intensity: Intensity in Channel 2

  • folder_name: Source folder

  • Additional metadata

File Location:

  • Saved in the same folder as your images

  • Filename: <folder_name>_intensity.csv

  • Check terminal output for exact path

Step 7: Saving and Exporting

Automatic Saves:

  • CSV files are automatically saved after intensity calculation

  • Naming format: <folder_name>_intensity.csv

Manual Saves:

If you made manual corrections (see Manual Corrections):

  1. Click Save button

  2. Corrections are stored for next time you load this image set

Exporting Visualizations:

To export images with overlays:

  1. In Napari menu: File → Save Selected Layer(s)

  2. Choose format (PNG recommended)

  3. Select layers to export

Analysis Without Segmentation

For spot-only analysis (no chromosome segmentation needed):

When to Use:

  • No DAPI channel available

  • Only analyzing spot co-localization

  • Chromosomes not relevant to your analysis

Setup:

  1. Check Skip Segmentation before loading images

  2. Load only Channel 1 and Channel 2 images

  3. DAPI is ignored even if present

Workflow:

  1. Load images (segmentation is skipped)

  2. Detect Channel 1 spots

  3. Detect Channel 2 spots

  4. Find common regions (based on spatial proximity)

  5. Measure intensities

Differences:

  • No chromosome boundaries

  • Spot detection uses entire image

  • Common regions based on spot proximity, not chromosome overlap

One-Click Analysis: Run All

Run All button

Run All button for automated processing

Once you’ve determined optimal thresholds:

  1. Configure channel identifiers

  2. Load images

  3. Adjust both threshold sliders

  4. Check/uncheck Skip Segmentation as needed

  5. Click Run All

What Happens:

Automatically executes all steps:

  • Segmentation (if not skipped)

  • Channel 1 spot detection

  • Channel 2 spot detection

  • Find common regions

  • Calculate intensities

  • Save results

Use Case:

Perfect for processing additional images with known-good parameters.

Parameters Reference

Channel Identifiers:

  • DAPI identifier (string)

  • Channel 1 identifier (string)

  • Channel 2 identifier (string)

Detection Thresholds:

  • DNA-FISH threshold (0-100, default: 50)

  • CENP-C threshold (0-100, default: 50)

Processing Options:

  • Skip segmentation (checkbox)

  • Post-processing options (if available)

Output Files:

  • <folder_name>_intensity.csv: Main results file

  • Optional: Saved segmentations and spot labels

Best Practices

Parameter Optimization:

  1. Start with default thresholds (50)

  2. Test on 2-3 representative images

  3. Adjust thresholds based on results

  4. Document optimal values for your imaging conditions

Quality Control:

  • Visually inspect segmentation results

  • Check spot detection for false positives/negatives

  • Use manual correction tools when needed

  • Save corrections for reproducibility

Documentation:

  • Record optimal threshold values

  • Note any imaging condition changes

  • Keep analysis parameters with results

  • Document manual corrections made

Next Steps