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Tutorial - MicroLive

Introduction

This tutorial provides comprehensive step-by-step instructions for all analysis workflows in the MicroLive GUI. We'll cover each tab in order, from basic image loading to advanced analysis and data export.

Prerequisites

Before starting, ensure you have:

  • Sample microscopy data (.lif or .tif format)
  • Basic understanding of your imaging parameters
  • Sufficient computational resources for your dataset

Tutorial 1: Import Tab - Image Loading and Visualization

Overview

Learn to load, visualize, and navigate through microscopy data with proper display settings.

Step 1: Application Launch and File Loading

  1. Launch the Application

    conda activate microlive
microlive

  2. Open Image Files

    • Click "Open File" button
    • Navigate to your microscopy file (.lif or .tif)
    • Select the file and click "Open"
    • For LIF files: multiple scenes will appear in the tree view
    • For TIFF files: single image will be loaded immediately

  3. Select Image Scene (LIF files only)

    • Expand the file in the tree view on the right
    • Click on the desired scene/image
    • The image will load and display in the main canvas

Step 2: Metadata Verification

  1. Check Image Information Panel

    • Review file name, dimensions, and channels
    • Verify frames, Z-slices, and pixel counts
    • Check bit depth and time intervals
    • Confirm voxel sizes (XY and Z)

  2. Handle Missing Metadata

If prompted, enter missing values:

  • PhysicalSizeX and PhysicalSizeY: Pixel size in nanometers (nm) for both X and Y dimensions
  • PhysicalSizeZ: Z-step size in nanometers (nm)
  • TimeIncrement: Time interval between frames in seconds (s)

These values are crucial for quantitative analysis and proper scaling of measurements.

Step 3: Navigation and Display Controls

  1. Time Navigation

    • Use the horizontal time slider to browse frames
    • Click "Play" button for automatic playback
    • Observe temporal dynamics of your sample

  2. Z-plane Navigation

    • Use the vertical Z-slider on the right of the image
    • Top position = maximum projection (recommended for tracking)
    • Lower positions = individual Z-planes

  3. Channel Selection

    • Click individual channel buttons (Ch0, Ch1, etc.)
    • Each channel displays with its assigned colormap
    • Green (Ch0), Magenta (Ch1), Yellow (Ch2)

  4. Merge Channels

    • Click "Merge Channels" for multi-channel overlay
    • Useful for assessing colocalization visually
    • Individual channel intensities blend additively

Step 4: Display Optimization

  1. Adjust Channel Parameters

    • Select channel tabs in the control panel
    • Adjust intensity percentiles (min: 0-50%, max: 90-100%)
    • Modify smoothing (high sigma for noise reduction)
    • Fine-tune low sigma for subtle enhancement

  2. Theme and Overlays

    • Toggle Dark/Light theme with the switch
    • Enable "Time" checkbox for timestamp overlay
    • Enable "Background" checkbox for segmentation overlay

Step 5: Export Options

  1. Export Current Image

    • Click "Export Image" for high-resolution PNG (300 DPI)
    • Choose filename and location
    • Current display settings are preserved

  2. Export Time-lapse Video

    • Click "Export Video" for MP4 or GIF format
    • All frames exported with current display settings
    • Scalebar included if voxel size is available

Expected Results

  • Properly loaded and calibrated microscopy data
  • Optimized display settings for visualization
  • Understanding of data structure and quality

Tutorial 2: Registration Tab - Correcting Sample Drift

Overview (Tutorial 2)

Correct for XY stage drift or sample movement between frames, ensuring that the same cell stays aligned across all time points before downstream analysis.

When to use: Run Registration after Import if your cells visibly drift or shift across frames. Skip this tab if your data is already stable.

Step 1: Navigate to Registration Tab

  1. Click the "Registration" tab (second tab, after Import)
  2. The interface shows two side-by-side panels:
    • Left: Original image — use this to draw an ROI
    • Right: Registered result — updates after registration runs

Step 2: Select a Reference Region (ROI)

  1. Click and drag on the left image panel to draw a rectangular ROI
    • The ROI should contain a stable, bright reference structure (e.g., a single cell body, a fiducial marker)
    • Avoid regions with moving particles — you want a structure that stays fixed
    • A cyan rectangle appears as you drag; the ROI status indicator turns green when confirmed
  2. If no ROI is drawn, clicking "Perform Registration" will use the full image (a warning will appear)

Step 3: Choose Registration Mode

Use the Mode dropdown to select the transformation type:

Mode Description When to Use
RIGID_BODY Rotation + translation (default) Most live-cell data
TRANSLATION X/Y shift only, no rotation Minimal stage drift
SCALED_ROTATION Rotation + scaling + translation Zoom drift
AFFINE Full affine (shear, scale, rotation) Complex distortions

Step 4: Perform Registration

  1. Click "▶ Perform Registration" (green button)
  2. A progress dialog shows percent completion frame by frame
  3. The right panel updates to show the registered image when complete
  4. The registered image is used automatically in all subsequent tabs

Step 5: Evaluate and Undo if Needed

  1. Compare panels: Use the time slider and playback button to check that motion is corrected
  2. Undo: Click "✕ Remove" to discard registration and revert to the original image
  3. Re-draw the ROI or change mode and re-register if results are unsatisfactory

Expected Results (Tutorial 2)

  • Stable alignment across all time frames
  • Registered image available for all subsequent analysis tabs
  • Clear visual comparison between original and corrected panels

Tutorial 3: Segmentation Tab - Cell Boundary Definition

Overview (Tutorial 3)

Define cellular regions for masking subsequent analyses, ensuring particles are analyzed only within cells of interest.

Step 1: Segmentation Setup

  1. Navigate to Segmentation Tab

    • Click the "Segmentation" tab
    • The interface shows image on left, controls on right

  2. Select Image Source

    • Choose appropriate channel for segmentation.
    • Use channel buttons to switch between channels
    • Use time slider to select representative frame

  3. Configure Maximum Projection

    • Check "Use Max Projection for Segmentation" if needed
    • Useful for thick samples or when cells extend through Z
    • Status label indicates current setting

The Segmentation tab contains five sub-tabs: Watershed, Cellpose, Manual, Import, and Edit. Use whichever method produces the cleanest mask for your data.

Step 2: Watershed Sub-tab (Automated, no deep learning)

  1. Click the "Watershed" sub-tab
  2. Adjust the Threshold Factor slider (0.5–2.0; default 1.0)
    • Higher values = more conservative/smaller masks
    • The slider updates the segmentation live as you drag
  3. Use the Size slider to expand (+) or shrink (−) the resulting mask in pixels
  4. Click "Run Watershed" to apply
  5. A cyan semi-transparent overlay with white contours shows the result

Step 3: Cellpose Sub-tab (Deep learning, recommended)

  1. Click the "Cellpose" sub-tab
  2. Set the expected cell diameter in pixels (read the pixel scale from the axis labels in the image panel)
  3. Choose cytoplasm and/or nucleus channels from the dropdowns
  4. Click "Run Cellpose (Cyto)" and/or "Run Cellpose (Nuc)"
  5. Click "Synchronize" to align cytosol and nucleus masks across cells
    • Only cells with a matched nucleus inside the cytosol are kept
  6. Optionally enable "Remove border cells", "Remove unpaired cells", or "Keep center cell only"

Step 4: Manual Sub-tab (Polygon drawing)

  1. Click the "Manual" sub-tab
  2. Click "Manual Segmentation" to enter polygon-draw mode
  3. Click points around the cell perimeter (clockwise or counter-clockwise)
    • Points are connected automatically
  4. Click "Finish Segmentation" to close the polygon and generate a mask
  5. Click "Clear Mask" to start over if needed

Step 5: Import Sub-tab (Load external mask)

  1. Click the "Import" sub-tab
  2. Click "Import Cytosol Mask" or "Import Nucleus Mask" to load a TIFF mask file
    • Mask must match image dimensions (Y × X, integer labels)
  3. Status labels turn green when a mask is successfully loaded

Step 6: Edit Sub-tab (Refine existing mask)

  1. Click the "Edit" sub-tab (available after any mask is created)
  2. Use the mask selector dropdown to choose which mask layer to edit
  3. Draw or erase regions using the brush tools
  4. Use "Undo" to revert the last change, "Reset" to discard all edits
  5. Click "Apply & Save Edits" to commit edits to the active mask

Step 7: Quality Control and Export

  1. Verify Segmentation Quality

    • Ensure mask covers intended cellular region
    • Check that background is properly excluded
    • Re-segment if boundaries are inaccurate

  2. Export Segmentation

    • Click "Export Image" for segmentation visualization
    • Click "Export Mask" for binary mask as TIFF

Expected Results (Tutorial 3)

  • Binary mask defining cellular region(s)
  • Quality segmentation for subsequent masking
  • Exported mask TIFF for documentation

Tutorial 4: Photobleaching Tab - Intensity Correction

Overview (Tutorial 4)

Correct for photobleaching artifacts that affect quantitative fluorescence measurements over time.

Step 1: Prerequisites Check

  1. Ensure Requirements are Met
    • Must have segmentation mask from previous step
    • Time-series fluorescence data required
    • Sufficient time points for fitting (>20 frames recommended)

Step 2: Photobleaching Analysis Setup

  1. Navigate to Photobleaching Tab

    • Click "Photobleaching" tab
    • Review available parameters

  2. Select Analysis Mode

    • Inside Cell: Use pixels within segmentation mask
    • Outside Cell: Use background pixels outside mask
    • Circular Region: Define custom circular analysis area

  3. Configure Parameters

    • Radius: Size of analysis region (for circular mode)

Step 3: Execute Correction

  1. Run Photobleaching Analysis

    • Click "Run Photobleaching" button
    • Wait for fitting to complete
    • Progress indicated in status

  2. Interpret Results

    • Left Panels: Show fitted decay curves for each channel
    • Right Panels: Compare original vs. corrected intensities
    • Fit Parameters: Decay rates and amplitudes displayed
    • Model Quality: Assess goodness of fit

Step 4: Evaluate Correction

  1. Check Correction Quality

    • Corrected data should show stable intensities
    • Original data shows declining intensities
    • Fit should capture the decay trend well

  2. Adjust if Needed

    • Try different model types if fit is poor
    • Adjust removed time points if early frames are problematic
    • Consider different analysis regions

Step 5: Apply Corrected Data

  1. Use in Subsequent Analysis

    • Photobleaching-corrected images now available
    • Select "Photobleaching Corrected" in tracking source
    • All subsequent quantitative analyses benefit from correction

  2. Export Results

    • Click "Export Photobleaching Image" for documentation
    • Save plots showing correction effectiveness

Expected Results (Tutorial 4)

  • Quantified photobleaching parameters
  • Corrected image stack for quantitative analysis
  • Documentation of correction effectiveness

Tutorial 5: Tracking Tab - Particle Detection and Trajectory Linking

Overview (Tutorial 5)

Detect particles and link them into trajectories for dynamic analysis.

Step 1: Tracking Setup and Image Source

  1. Navigate to Tracking Tab

    • Click "Tracking" tab
    • Left panel shows image display, right panel shows parameters

  2. Configure Image Source

    • Select "Original Image" or "Photobleaching Corrected"
    • Use corrected images for quantitative intensity measurements
    • 2D projection checkbox controls Z-processing (default on, i.e. 3D detection is used unless you disable 2D)

  3. Set Display Parameters

    • Adjust "Min Int" and "Max Int" percentiles
    • Optimize contrast for particle visualization
    • Select appropriate channel for detection

Step 2: Threshold Selection

  1. Generate Threshold Histogram

    • Navigate through frames to see typical intensity
    • Histogram appears when parameters are set
    • Shows intensity distribution within segmentation mask

  2. Set Detection Threshold

    • Use threshold slider to set detection level
    • Red line shows current threshold on histogram
    • Aim for 3-5× background level
    • Balance sensitivity vs. false detections
    • Alternatively: Click the "Auto" button for automated threshold detection using a hybrid approach that combines methods from Big-FISH and TrueSpot
    • For inhibitor experiments: Enable the "Fixed" button (next to Auto) to lock the threshold from frame 0 across all frames, preventing false detections when signal decreases over time

Step 3: Detection Parameters

  1. Spot Size Configuration

    • YX Spot Size: Expected particle size in pixels (typically 5-9)
    • Z Spot Size: Axial extent in pixels (typically 3-5)
    • Must be odd numbers (automatically adjusted)

  2. Clustering Parameters

    • Cluster Radius: Distance for grouping spots (nm)
    • Max Cluster Size: Maximum spots per cluster (0 = no limit)
    • Helps handle aggregated particles

Step 4: Trajectory Linking Parameters

  1. Search and Memory Settings

    • Max Range Search: Maximum distance particles can move between frames
    • Memory: Frames a particle can disappear (typically 1-3)
    • Min Length Trajectory: Minimum trajectory duration (frames)

  2. Advanced Options

    • 2D Projection: Use maximum projection for detection
    • Fixed Size Intensity: Use consistent aperture for measurements
    • 3D Coordinates: Include Z in linking (if available)

Step 5: Detection and Tracking Execution

  1. Test Detection

    • Click "Single Frame" to test current parameters
    • Red circles show detected particles
    • Adjust threshold if too few/many detections

  2. Detect All Frames

    • Click "Detection" for complete detection
    • Progress dialog shows processing status
    • Review detection overlay across time

  3. Link Trajectories

    • Click "Tracking" to link detections into trajectories
    • Most computationally intensive step
    • Creates complete trajectory dataset

Step 6: Visualization and Quality Control

  1. Enable Visualization Options

    • Check "Trajectories" to show particle paths
    • Check "Cluster Size" to show clustering info
    • Check "Particle ID" to show trajectory numbers
    • Check "Time Stamp" for temporal reference

  2. Quality Assessment

    • Look for broken trajectories (insufficient linking)
    • Look for incorrect linking (excessive linking)
    • Use play button to observe trajectory dynamics

  3. Random Control Spots

    • Enable "Generate Random Spots" for controls
    • Specify number of random locations
    • Provides background measurements for comparison

Step 7: Export Tracking Results

  1. Export Data

    • Click "Export DataFrame" for CSV trajectory data
    • Contains all particle measurements and properties
    • Use default naming or specify custom filename

  2. Export Visualizations

    • Click "Export Image" for current frame visualization
    • Click "Export Video" for complete trajectory movie
    • Includes all enabled overlays and colormaps

Expected Results (Tutorial 5)

  • Complete particle trajectory dataset
  • Quantitative measurements for each detection
  • Visual documentation of tracking quality
  • CSV file ready for further analysis

Tutorial 6: MSD Tab - Mean Squared Displacement Analysis

Overview (Tutorial 6)

Calculate Mean Squared Displacement (MSD) curves and diffusion coefficients from particle trajectories. MSD analysis reveals whether particles undergo free diffusion, confined diffusion, or directed motion.

Step 1: Prerequisites

  1. Data Requirements
    • Completed particle tracking (Tracking tab)
    • Trajectories with sufficient length (>10 frames recommended)
    • Accurate pixel size and time interval metadata

Step 2: Navigate to MSD Tab

  1. Click the "MSD" tab (between Tracking and Distribution)
  2. Left panel shows the MSD plot canvas; right panel shows parameters and results

Step 3: Select Tracking Channel

  1. Use the Tracking Channel dropdown to select the channel whose trajectories to analyze
    • Only channels with linked trajectories appear in the list

Step 4: Configure MSD Parameters

  1. Fit Points: Number of lag-time points used for the linear diffusion fit (default: 20)
    • Fewer points = fit dominated by short lags (more accurate for free diffusion)
    • More points = fit includes longer lags (useful for confined/directed motion detection)
  2. Mode: Automatically detected from trajectory dimensionality (2D or 3D)
    • Shown as a read-only label: "Mode: Auto-detect"

Step 5: Calculate MSD

  1. Click "Calculate MSD" (green button)
  2. MSD curves are plotted for each trajectory and the ensemble mean is overlaid
  3. Results are displayed in the right panel:
    • D (μm²/s): Diffusion coefficient in physical units (requires calibrated voxel size)
    • D (px²/s): Diffusion coefficient in pixel units
    • R²: Goodness of linear fit
    • N: Number of trajectories analyzed

Step 6: Interpret Results

  1. Linear MSD vs. lag time → Free (Brownian) diffusion
  2. Sub-linear (flattening) MSD → Confined diffusion
  3. Super-linear (accelerating) MSD → Directed/active transport
  4. Toggle "Log-Log Scale" to visualize the MSD power-law exponent (α = 1 for free diffusion)

Step 7: Export MSD Results

  1. Click "Export DataFrame" to save per-trajectory MSD values as CSV
  2. Click "Export Plot" to save the MSD figure as a PNG

Expected Results (Tutorial 6)

  • Ensemble MSD curve with per-trajectory overlay
  • Diffusion coefficient D and R² fit quality
  • Exported CSV and plot for publication

Tutorial 7: Distribution Tab - Statistical Analysis of Particle Properties

Overview (Tutorial 7)

Generate histograms and statistical summaries of measured particle properties.

Step 1: Data Requirements

  1. Prerequisites
    • Must have completed particle tracking
    • Non-empty trajectory dataset required
    • Multiple particles recommended for meaningful statistics

Step 2: Distribution Analysis Setup

  1. Navigate to Distribution Tab

    • Click "Distribution" tab
    • Left panel for plots, right panel for controls

  2. Select Data Field

    • Field dropdown: Choose measurement to analyze
      • spot_int: Integrated intensity (most common)
      • psf_amplitude: Fitted peak intensity
      • psf_sigma: Particle size/width
      • snr: Signal-to-noise ratio
      • total_spot_int: Total intensity including background
      • cluster_size: Number of spots in cluster

  3. Select Channel

    • Choose channel for analysis
    • Must match field selection (e.g., spot_int_ch_0)
    • Different channels may show different distributions

Step 3: Histogram Configuration

  1. Set Percentile Range

    • Min Percentile: Lower bound for histogram (0-50%)
    • Max Percentile: Upper bound for histogram (50-100%)
    • Helps exclude outliers and focus on main distribution

  2. Generate Histogram

    • Click "Plot Histogram" to create distribution plot
    • 60 bins used by default
    • Statistics displayed: mean and median values

Step 4: Interpretation

  1. Analyze Distribution Shape

    • Normal distribution suggests homogeneous population
    • Bimodal distribution may indicate subpopulations
    • Skewed distribution suggests measurement artifacts or biology

  2. Compare Across Conditions

    • Generate histograms for different channels
    • Compare different measurement fields
    • Document differences between experimental conditions

Step 5: Export Results

  1. Save Distribution Plots
    • Click "Export Distribution Image"
    • High-resolution PNG with statistics
    • Include in publications or reports

Expected Results (Tutorial 7)

  • Quantitative distribution of particle properties
  • Statistical summary (mean, median)
  • Visual representation suitable for publication

Tutorial 8: Time Course Tab - Temporal Dynamics Analysis

Overview (Tutorial 8)

Analyze how particle properties change over time, revealing dynamic processes.

Step 1: Time Course Setup

  1. Navigate to Time Course Tab

    • Click "Time Course" tab
    • Requires completed tracking data

  2. Select Analysis Parameters

    • Channel: Choose channel for analysis
    • Data Type: Select measurement type
      • particles: Number of detected particles per frame
      • spot_int: Average spot intensity over time
      • psf_amplitude: Average amplitude over time
      • Other measurements available

Step 2: Configure Analysis Range

  1. Set Percentile Filters
    • Min Percentile: Exclude lowest values (typically 5%)
    • Max Percentile: Exclude highest values (typically 95%)
    • Helps remove outliers and focus on main population

Step 3: Generate Time Course

  1. Execute Analysis

    • Click "Plot Time Course" button
    • Processing time depends on dataset size
    • Multiple traces may appear for different particles/conditions

  2. Interpret Results

    • Y-axis: Selected measurement values
    • X-axis: Time (frames or seconds if calibrated)
    • Trends: Look for increases, decreases, or oscillations
    • Variability: Assess consistency across time

Step 4: Export Time Course Data

  1. Save Time Course Plots
    • Click "Export Time Courses Image"
    • High-resolution plots with proper axes labels
    • Suitable for presentations and publications

Expected Results (Tutorial 8)

  • Temporal profiles of particle properties
  • Identification of dynamic processes
  • Quantitative time course data for further analysis

Tutorial 9: Correlation Tab - Temporal Correlation Analysis

Overview (Tutorial 9)

Analyze temporal correlations in particle dynamics to extract kinetic information and assess particle interactions.

Step 1: Correlation Analysis Prerequisites

  1. Data Requirements

    • Completed particle tracking with good quality trajectories
    • Sufficient time points (>50 frames recommended)
    • Long trajectories provide better correlation estimates

  2. Navigate to Correlation Tab

    • Click "Correlation" tab
    • Left panel for plots, right panel for parameters

Step 2: Select Correlation Type

  1. Autocorrelation Analysis

    • Select "Auto" radio button
    • Analyzes single channel temporal dynamics
    • Reveals characteristic time scales of fluctuations

  2. Cross-correlation Analysis

    • Select "Cross" radio button
    • Compares dynamics between two channels
    • Identifies temporal relationships and delays

Step 3: Channel and Field Selection

  1. Select Channels

    • Check appropriate channel checkboxes
    • For autocorrelation: select one channel
    • For cross-correlation: select two channels

  2. Choose Data Field

    • Field dropdown: Select measurement for correlation
    • spot_int: Most common choice for intensity correlations
    • psf_amplitude: Alternative intensity measure
    • Other fields available for specialized analyses

Step 4: Configure Correlation Parameters

  1. Data Quality Settings

    • Min % Data: Require minimum data completeness per trajectory
    • Threshold: Decorrelation threshold for analysis
    • Remove outliers: Filter extreme values

  2. Fit Configuration

    • Fit Type: Choose "Linear" or "Exponential"
    • Index Max Lag for Plot: Set range for visualization
    • Index Max Lag for Fit: Set range for curve fitting
    • Start Lag: Usually set to 1 to exclude τ=0

  3. Display Options

    • Min/Max Percentile: Set plot range
    • Normalize: Normalize correlation amplitude
    • Baseline correction: Remove systematic trends

Step 5: Execute Correlation Analysis

  1. Run Correlation Calculation

    • Click "Run" button
    • Processing time depends on data size and lag range
    • Progress indicated during calculation

  2. Interpret Autocorrelation Results

    • G(τ) vs τ: Correlation amplitude vs. time lag
    • Decorrelation time: Time scale of intensity fluctuations
    • Amplitude: Magnitude of fluctuations
    • Exponential fit: Provides characteristic time constant

  3. Interpret Cross-correlation Results

    • Peak position: Time delay between channels
    • Peak amplitude: Strength of correlation
    • Asymmetry: Indicates directional relationships

Step 6: Advanced Analysis Options

  1. Fitting Models

    • Linear: For initial analysis or non-exponential behavior
    • Exponential: Most common for single-component kinetics
    • Fit parameters provide quantitative kinetic information

  2. Multi-Tau Mode

    • Enable the "Multi-Tau" checkbox for logarithmically-spaced lag bins
    • Compresses long lag ranges into fewer points, improving signal-to-noise at long lags
    • Recommended when analyzing slow processes or very long trajectories
    • Configure via Multi-Tau Raw Points and Bins per Stage parameters

  3. Quality Assessment

    • Error bars: Indicate statistical uncertainty
    • Fit quality: Assess how well model describes data
    • Smoothed curves: Help identify trends in noisy data

Step 7: Export Correlation Results

  1. Save Correlation Analysis
    • Click "Export Correlation Image"
    • High-resolution plots with fit parameters
    • Include both raw data and fitted curves

Expected Results (Tutorial 9)

  • Quantitative correlation functions
  • Kinetic parameters from curve fitting
  • Temporal relationships between channels
  • Publication-quality correlation plots

Tutorial 10: Colocalization Tab - Automated Spatial Analysis

Overview (Tutorial 10)

Quantify spatial relationships between particles in different channels using automated methods.

Step 1: Colocalization Prerequisites

  1. Data Requirements
    • Multi-channel microscopy data (minimum 2 channels)
    • Completed particle tracking on reference channel
    • Good registration between channels

Step 2: Colocalization Setup

  1. Navigate to Colocalization Tab

    • Click "Colocalization" tab
    • The tab contains four sub-tabs: Visual, Verify Visual, Distance, and Verify Distance
    • Start with the Visual sub-tab for crop-matrix colocalization

  2. Select Analysis Channels

    • Reference: Channel containing tracked particles
    • Colocalize: Target channel for colocalization analysis
    • Typically reference is the tracking channel

Step 3: Choose Analysis Method

  1. Machine Learning Method

    • Select "ML" radio button
    • Uses trained neural network for classification
    • ML Threshold: Set confidence threshold (0.5-1.0)
    • Higher thresholds = more stringent colocalization

  2. Intensity-Based Method

    • Select "Intensity" radio button
    • Uses signal-to-noise ratio criteria
    • Threshold: Set SNR threshold (typically 3-5)
    • Higher thresholds = more stringent requirements

Step 4: Configure Display Options

  1. Crop Matrix Settings
    • Columns: Number of columns in result matrix
    • More columns = more crops displayed
    • Balance between detail and overview

Step 5: Execute Colocalization Analysis

  1. Run Analysis

    • Click "Run" button
    • Processing generates crop matrix around each particle
    • Red borders indicate colocalized spots

  2. Interpret Results

    • Colocalization Percentage: Quantitative measure
    • Visual Matrix: Side-by-side channel comparison
    • Color Coding: Flagged spots highlighted
    • Crop Spacing: Organized grid layout

Step 6: Quality Control

  1. Assess Analysis Quality

    • Visually inspect flagged vs. non-flagged spots
    • Check for false positives/negatives
    • Consider adjusting thresholds if needed

  2. Interactive Zoom

    • Hover over matrix for magnified view
    • Red rectangle shows current zoom region
    • Detailed inspection of individual spots

Step 7: Export Colocalization Results

  1. Export Quantitative Data

    • Click "Export Data" for CSV summary
    • Contains percentages and spot counts
    • Includes method and threshold information

  2. Export Visualization

    • Click "Export Image" for crop matrix
    • High-resolution documentation of results
    • Includes colocalization percentage in title

Expected Results (Tutorial 10)

  • Quantitative colocalization percentage
  • Visual matrix showing analysis results
  • CSV file with detailed statistics
  • Publication-ready visualization

Distance Sub-tab

The Distance sub-tab computes pairwise Euclidean distances between spots in two channels:

  1. Select source and target channels from the dropdowns
  2. Set the distance threshold (in nm) for colocalization calls
  3. Click "Run Distance Colocalization"
  4. Use the frame slider and playback to review distance overlays frame by frame
  5. Click "Export Data" or "Export Image" for results

Verify Visual and Verify Distance Sub-tabs

These sub-tabs allow manual expert validation of the automated results:

  1. Click "Verify Visual" or "Verify Distance" sub-tab
  2. Click "Populate" to load the automated colocalization results
    • Each particle pair appears as a thumbnail showing both channels
  3. Check or uncheck boxes to accept or reject individual colocalization calls
  4. Statistics update in real time (total, colocalized, percentage)
  5. Click "Cleanup" to uncheck all and start fresh
  6. Click "Export Data" to save the manually verified CSV

Expected Results (Tutorial 10)

  • Quantitative colocalization percentage (automated and manually verified)
  • Visual matrix showing analysis results
  • CSV files with detailed statistics (Visual, Distance, and manual variants)
  • Publication-ready visualizations

Tutorial 11: Tracking Visualization Tab - Advanced Particle Inspection

Overview (Tutorial 11)

Detailed visualization and analysis of individual particle trajectories with multi-channel context.

Step 1: Tracking Visualization Setup

  1. Navigate to Tracking Visualization Tab

    • Click "Tracking Visualization" tab
    • Requires completed particle tracking

  2. Populate Particle List

    • Particle list shows all tracked particles
    • Listed by particle ID number
    • Select individual particles for detailed analysis

Step 2: Particle Selection and Display

  1. Select Particle of Interest

    • Click particle in list (right panel)
    • Main display updates to show selected particle
    • Red circle highlights particle position

  2. Multi-panel Display

    • Left Panel: Full field view with particle marked
    • Right Panels: Cropped views of each channel
    • Synchronized: All panels show same time point

Step 3: Display Optimization

  1. Intensity Controls

    • Adjust "Min Int" and "Max Int" percentiles
    • Optimize contrast for particle visibility
    • Apply to all channels simultaneously

  2. Channel Selection

    • Click individual channel buttons for single-channel view
    • Click "Merge Channels" for overlay view
    • Toggle between visualization modes

Step 4: Temporal Navigation

  1. Time Control

    • Use time slider for frame-by-frame analysis
    • Play button for automatic progression
    • Observe particle dynamics over time

  2. Display Options

    • Remove Background: Apply segmentation mask
    • Show Scalebar: Add scale reference
    • Show Time Stamp: Display temporal information

Step 5: Advanced Analysis

  1. Trajectory Inspection

    • Follow particle movement through time
    • Assess trajectory quality and continuity
    • Identify potential tracking errors

  2. Multi-channel Comparison

    • Compare particle appearance across channels
    • Assess intensity relationships
    • Identify channel-specific behaviors

Step 6: Export Detailed Results

  1. Export Single Frame

    • Click "Export Image" for current view
    • Includes all display settings and overlays
    • Documents specific particle behavior

  2. Export Particle Movie

    • Click "Export Video" for temporal sequence
    • Shows selected particle dynamics
    • Useful for presentations and detailed analysis

Expected Results (Tutorial 11)

  • Detailed inspection of individual particle behavior
  • Multi-channel context for particle analysis
  • High-quality visualizations for documentation
  • Videos showing particle dynamics

Tutorial 12: Export Tab - Comprehensive Data Management

Overview (Tutorial 12)

Organize and export all analysis results in a structured, documented format for sharing and archival.

Step 1: Export Preparation

  1. Complete Desired Analyses

    • Finish all relevant analysis tabs
    • Ensure results are satisfactory
    • Document any special conditions or issues

  2. Navigate to Export Tab

    • Click "Export" tab
    • Review comprehensive export options

Step 2: Documentation and Comments

  1. Select Predefined Comments

    • Use dropdown to select common observations:
      • "Few or no spots were detected"
      • "Aggregates in cell"
      • "Cell died during acquisition"
      • "Cell divided during acquisition"
      • "The cell goes out of focus"
      • "Error during microscope acquisition"
      • "Error during tracking. Spots not linked correctly"

  2. Add Custom Comments

    • Select "Custom" for specific observations
    • Document experimental conditions
    • Note any analysis challenges or decisions
    • Include relevant methodological details

Step 3: Select Export Items

  1. Review Available Exports

    • Export Entire Image as OME-TIF: Original data with metadata in tif format
    • Export Displayed Image: Current visualization
    • Export Segmentation Image: Segmentation overlay
    • Export Mask as TIF: Binary segmentation mask
    • Export Photobleaching Image: Correction analysis plots
    • Export Tracking Data: Complete trajectory CSV
    • Export Tracking Image: Tracking visualization
    • Export Distribution Image: Histogram analysis
    • Export Time Course Image: Temporal analysis plots
    • Export Correlation Image: Correlation analysis
    • Export Colocalization Image: Colocalization matrix
    • Export Colocalization Data: Colocalization CSV
    • Export Manual Colocalization Image: Manual verification
    • Export Manual Colocalization Data: Manual CSV
    • Export Metadata File: Complete analysis parameters
    • Export User Comments: User comments as a text file
    • Export Random Spots Data: Control measurements for random positions inside the mask

  2. Use Selection Tools

    • Select All: Check all available exports
    • Deselect All: Clear all selections
    • Individual Selection: Choose specific items

Step 4: Execute Batch Export

  1. Choose Export Location

    • Click "Export Selected Items"
    • Select parent directory for export
    • Organized subfolder created automatically

  2. Folder Organization

    • Results folder named with file and image identifiers
    • All selected items exported with consistent naming
    • Metadata file includes complete parameter documentation

Step 5: Verify Export Completeness

  1. Review Export Folder

    • Check that all selected items were exported
    • Verify file naming consistency
    • Confirm metadata file contains all parameters

  2. Quality Assurance

    • Open key files to verify integrity
    • Check that CSV files contain expected data
    • Ensure images display correctly

Step 6: Data Management Best Practices

  1. File Organization

    • Use consistent naming conventions
    • Include date and experiment identifiers
    • Maintain folder structure across experiments

  2. Documentation Standards

    • Always export metadata with results
    • Include user comments for context
    • Document any deviations from standard protocols

  3. Backup and Archival

    • Create backups of exported results
    • Store raw data separately from analysis results
    • Maintain version control for analysis parameters

Expected Results (Tutorial 12)

  • Organized folder containing all analysis results
  • Complete documentation of analysis parameters
  • Consistent file naming and structure
  • User comments and metadata preserved
  • Ready for sharing, publication, or archival

Troubleshooting Common Issues

Loading and Display Issues

Problem: Image fails to load or displays incorrectly Solutions:

  • Check file format compatibility (.lif, .tif, .ome.tif)
  • Verify file path and permissions
  • Ensure sufficient memory for large files
  • Check metadata completeness

Segmentation Problems

Problem: Poor segmentation quality Solutions:

  • Try different channels for segmentation
  • Adjust watershed threshold factor
  • Use maximum projection for thick samples
  • Consider manual segmentation for complex shapes

Detection Issues

Problem: Too few particles detected Solutions:

  • Lower detection threshold
  • Check segmentation mask coverage
  • Verify channel selection
  • Adjust spot size parameters

Problem: Too many false detections Solutions:

  • Raise detection threshold
  • Improve segmentation to exclude background
  • Adjust spot size to match particle size
  • Check for imaging artifacts

Tracking Problems

Problem: Broken trajectories Solutions:

  • Increase maximum search range
  • Add memory frames for tracking gaps
  • Improve detection consistency
  • Check for sample drift

Problem: Incorrect particle linking Solutions:

  • Decrease search range to prevent over-linking
  • Reduce memory frames
  • Improve detection specificity
  • Check for high particle density issues

Performance Issues

Problem: Slow processing or memory errors Solutions:

  • Use 2D projection mode
  • Process smaller regions or time ranges
  • Close unused files and applications
  • Increase system memory
  • Use lower resolution for initial optimization

Analysis Quality Issues

Problem: Poor correlation results Solutions:

  • Increase minimum trajectory length
  • Improve tracking quality
  • Check temporal sampling rate
  • Verify sufficient data points per trajectory

Problem: Inconsistent colocalization Solutions:

  • Verify channel registration
  • Check detection parameters consistency
  • Use manual verification for validation
  • Consider using ML method for better accuracy

Best Practices Summary

Data Quality

  1. Start with high-quality data: Proper acquisition parameters, sufficient signal-to-noise ratio
  2. Verify metadata: Ensure pixel sizes and time intervals are correct
  3. Optimize imaging: Balance temporal resolution, spatial resolution, and photobleaching

Analysis Workflow

  1. Sequential approach: Follow tab order for logical workflow progression
  2. Parameter testing: Test on subsets before full analysis
  3. Quality control: Visually inspect results at each step
  4. Documentation: Export parameters and add comments throughout

Result Validation

  1. Visual inspection: Always verify automated results visually
  2. Control experiments: Include appropriate negative and positive controls
  3. Reproducibility: Test parameter sensitivity and biological replicates
  4. Statistical rigor: Use appropriate sample sizes and statistical tests

Data Management

  1. Consistent naming: Use systematic file and folder naming
  2. Complete export: Always export metadata with results
  3. Version control: Track analysis parameters across iterations
  4. Backup strategy: Maintain copies of raw data and analysis results

Publication Preparation

  1. Method documentation: Export complete parameter sets
  2. Visual documentation: Export high-quality figures
  3. Statistical reporting: Include appropriate error bars and sample sizes
  4. Reproducibility: Provide sufficient detail for replication

For additional support, consult the User Guide and API Reference documentation.