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Hoxa11 Gene Expression Analysis Tutorial

Welcome to the comprehensive guide for analyzing Hoxa11 gene expression using LimbLab! This tutorial will walk you through the complete pipeline for processing and visualizing 3D limb data with Hoxa11 expression.

🎯 Objective

The goal of this tutorial is to analyze Hoxa11 gene expression in mouse limb development using Hybridization Chain Reaction (HCR) data. Hoxa11 is a crucial gene involved in limb patterning and development. By analyzing it in 3D, we can gain insights that might be missed in traditional 2D projections.

What you'll learn: - Setting up experiments in LimbLab - Processing raw volume data - Extracting 3D surfaces - Staging limbs automatically - Aligning with reference templates - Creating publication-ready visualizations

📁 Data Overview

Dataset: Hoxa11 HCR expression data
Location: example_data/hoxa11_raw_data/
Channels: - DAPI (nuclear staining) - Hoxa11 (gene expression)

Files: - HCR11_HOXA11_l1_dapi_488_LH.tif - DAPI channel - HCR11_HOXA11_l1_hoxa11_647_LH.tif - Hoxa11 channel

Download the data

On your terminal (MacOS, WSL or Linux), create a new folder.

mkdir example_data
mkdir example_data/hoxa11_raw_data
Then, you go to: XX From here you can download the needed files and locate them to the folder example_data/hoxa11_raw_data/

🚀 Step-by-Step Pipeline

Step 1: Create Experiment Structure

First, we need to create a new experiment folder to keep our raw data safe and organized.

mkdir case_studies
limb create-experiment case_studies/hoxa11_pipeline

What happens: LimbLab creates a new directory structure and initializes a pipeline.log file to track all processing steps.

Interactive prompts: - Limb side: Select L (Left) - Limb position: Select H (Hindlimb) - Microscope spacing: Use default 0.65 0.65 2.0

Expected output: 

✅ Experiment created: case_studies/hoxa11_pipeline
📝 Pipeline log initialized

Your pipeline.log should contain: 

BASE ./case_studies/hoxa11_pipeline
SIDE L
POSITION H
SPACING 0.65 0.65 2.0

Step 2: Clean DAPI Volume

The DAPI channel provides the structural reference for the limb. We need to clean it to remove noise and artifacts.

limb clean-volume case_studies/hoxa11_pipeline example_data/hoxa11_raw_data/HCR11_HOXA11_l1_dapi_488_LH.tif dapi

What happens: 1. LimbLab loads the raw DAPI volume 2. An interactive plotter appears showing the volume histogram 3. You select threshold values to remove background noise 4. The volume is processed with smoothing and filtering

Interactive steps: 1. Histogram analysis: Examine the intensity distribution 2. Threshold selection: Click to set bottom and top isovalues 3. Preview: Review the cleaned volume 4. Confirm: Accept the processing parameters

Processing details: - Gaussian smoothing: (6, 6, 6) - Frequency cutoff: 0.05 - Output size: (512, 512, 296) - Volume reduction: ~80% (typical)

Expected result: 

✅ DAPI volume cleaned and saved
📊 Volume size reduced from 1.2GB to 240MB
📝 Pipeline log updated

Step 3: Clean Hoxa11 Volume

Now we process the Hoxa11 gene expression channel using the same cleaning pipeline.

limb clean-volume case_studies/hoxa11_pipeline example_data/hoxa11_raw_data/HCR11_HOXA11_l1_hoxa11_647_LH.tif hoxa11

What happens: Same cleaning process as DAPI, but optimized for gene expression data.

Key differences: - Different threshold values (typically higher for gene expression) - Same smoothing and filtering parameters - Maintains spatial relationship with DAPI channel

Expected result: 

✅ Hoxa11 volume cleaned and saved
📊 Gene expression preserved
📝 Pipeline log updated

Step 4: Extract 3D Surface

We create a 3D surface mesh from the DAPI volume for further analysis and visualization.

limb extract-surface case_studies/hoxa11_pipeline/

What happens: 1. LimbLab loads the cleaned DAPI volume 2. Interactive isovalue selection for surface extraction 3. Surface mesh generation using marching cubes algorithm 4. Mesh decimation for performance optimization

Interactive steps: 1. Isovalue selection: Choose the intensity threshold for surface 2. Surface preview: Review the generated mesh 3. Quality check: Ensure surface captures limb morphology

Technical details: - Algorithm: Marching cubes - Decimation: 0.5% of original points - Format: VTK file - File size: ~2-5MB

Expected result: 

✅ Surface mesh extracted
📊 Mesh: 15,432 vertices, 30,864 faces
💾 Saved as: case_studies/hoxa11_pipeline/HCR11_HOXA11_l1_dapi_488_LH_surface.vtk

Step 5: Stage the Limb

Determine the developmental stage of the limb using our automated staging algorithm.

limb stage case_studies/hoxa11_pipeline/

What happens: 1. Interactive 3D viewer opens with the limb surface 2. You place points along the limb's long axis 3. A spline is fitted through the points 4. The algorithm calculates the developmental stage

Interactive controls: - Left click: Add point - Right click: Remove point
- 'c': Clear all points - 's': Stage the limb - 'r': Reset camera - 'q': Quit

Staging process: 1. Place 5-10 points along the limb's proximal-distal axis 2. Focus on the digit-forming region 3. Click 's' to calculate stage 4. Review the staging result

Step 6: Align with Reference

Align the limb with a reference template of the same stage for comparative analysis.

limb align case_studies/hoxa11_pipeline/

What happens: 1. Reference limb of stage 25.3 is loaded 2. Interactive 3D viewer shows both limbs 3. You manually align your limb with the reference 4. Transformation matrix is calculated and saved

Interactive alignment: - Mouse: Rotate, pan, zoom - 'a': Apply transformation - 'r': Reset alignment - Close window: Save transformation

Alignment benefits: - Enables comparative analysis - Standardizes orientation - Facilitates multi-sample studies

Expected result: 

✅ Limb aligned with reference
📊 Transformation matrix saved
📝 Pipeline log updated

Step 7: Visualize Hoxa11 Expression

Create publication-ready visualizations of the Hoxa11 gene expression.

7.1 3D Isosurface Visualization

limb vis isosurfaces case_studies/hoxa11_pipeline HOXA11

What happens: 1. Interactive isovalue selection for Hoxa11 expression 2. 3D surface rendering with color mapping 3. High-quality visualization with lighting and materials

Visualization features: - Color mapping: Expression intensity to color - Transparency: Adjustable opacity - Lighting: Realistic 3D lighting - Export: High-resolution images

Expected output: 

🎨 3D isosurface rendered
📊 Expression range: 0.2 - 0.8
💾 Image saved: case_studies/hoxa11_pipeline/hoxa11_isosurface.png

7.2 2D Slab Visualization

limb vis slab case_studies/hoxa11_pipeline HOXA11

What happens: 1. Interactive 2D slicing through the 3D volume 2. Dynamic slab adjustment 3. Real-time expression visualization

Interactive features: - Mouse wheel: Adjust slab thickness - Mouse drag: Move slab position - Color scale: Adjust expression range - Export: Save current view

📊 Results and Analysis

Expected Outcomes

After completing this tutorial, you should have:

  1. Processed data:
  2. Cleaned DAPI and Hoxa11 volumes
  3. 3D surface mesh
  4. Staging results

  5. Alignment transformation

  6. Visualizations:

  7. 3D isosurface of Hoxa11 expression
  8. 2D slab projections

  9. Publication-ready images

  10. Analysis insights:

  11. Limb developmental stage
  12. Spatial distribution of Hoxa11
  13. Expression patterns relative to limb morphology

Data Files Generated

case_studies/hoxa11_pipeline/
├── pipeline.log                    # Processing log
├── HCR11_HOXA11_l1_dapi_488_LH_cleaned.tif    # Cleaned DAPI
├── HCR11_HOXA11_l1_hoxa11_647_LH_cleaned.tif  # Cleaned Hoxa11
├── HCR11_HOXA11_l1_dapi_488_LH_surface.vtk    # 3D surface
├── staging.txt                     # Staging results
├── transformation_matrix.txt       # Alignment data
└── visualizations/                 # Generated images
    ├── hoxa11_isosurface.png
    └── hoxa11_slab.png

Troubleshooting

Common issues and solutions:

  1. Volume too large to load:
  2. Use the --size parameter to reduce output size

  3. Example: --size 256,256,148

  4. Poor surface quality:

  5. Adjust isovalues during surface extraction

  6. Try different threshold values

  7. Staging fails:

  8. Ensure points are placed along the limb AER

  9. Use more points for better accuracy

  10. Alignment issues:

  11. Start with gross alignment, then refine
  12. Use the reset function if needed

🔬 Scientific Context

Hoxa11 in Limb Development

Hoxa11 is a homeobox gene that plays a crucial role in: - Proximal-distal patterning of the limb - Digit formation and specification - Joint development and segmentation

3D Analysis Advantages

Compared to 2D sections, 3D analysis provides: - Complete spatial context of gene expression - Quantitative volume measurements - Better understanding of expression gradients - More accurate comparative analysis

This tutorial demonstrates the power of LimbLab for 3D gene expression analysis. The same pipeline can be applied to any gene or marker of interest in limb development research.