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Getting Help with LimbLab

Need assistance with LimbLab? You've come to the right place! This guide provides multiple ways to get help, from quick answers to detailed support.

🚀 Quick Start Help

First Time User?

  1. Check the Quick Start Guide - Get up and running in minutes
  2. Follow the Hoxa11 Tutorial - Complete step-by-step example
  3. Review the CLI Documentation - Command reference with examples

Getting Support

Direct Contact

Primary Support Email: laura.avino@embl.es

What to include in your email:

  • Subject: Clear description of the issue
  • LimbLab version: limb --version
  • Operating system: Windows/macOS/Linux version
  • Error message: Copy the complete error text
  • Steps to reproduce: Detailed description of what you did
  • Expected vs. actual behavior: What you expected vs. what happened
  • Data description: Brief description of your data (format, size, etc.)

Example email:

Subject: Volume processing fails with large TIFF files

Hi,

I'm having trouble processing large volume files with LimbLab.

Version: 0.2.0
OS: macOS 14.0
Error: "MemoryError: Unable to allocate array"

Steps:
1. Created experiment: limb create-experiment test
2. Tried to clean volume: limb clean-volume test large_file.tif DAPI
3. Got memory error after 5 minutes

The file is 2.5GB TIFF, 2048x2048x512 pixels.
Expected: Successful processing
Actual: Memory error

Any help would be appreciated!

Thanks,
[Your name]

Troubleshooting Guide

Installation Help

Common Installation Issues

"pip install limb fails" 

# Try upgrading pip first
pip install --upgrade pip

# Install with verbose output
pip install limb -v

# Check Python version (requires 3.8+)
python --version

"ImportError: No module named 'limb'" 

# Check if installed correctly
pip list | grep limb

# Try installing in user space
pip install --user limb

# Check Python environment
which python
which pip

"Permission denied" errors 

# Use virtual environment
python -m venv limblab_env
source limblab_env/bin/activate  # On Windows: limblab_env\Scripts\activate
pip install limb

CLI Troubleshooting

Command Not Found

# Check if limb is in PATH
which limb

# Try running with python -m
python -m limb --help

# Reinstall if necessary
pip uninstall limb
pip install limb

Parameter Errors

# Check command help
limb clean-volume --help

# Verify parameter format
limb clean-volume experiment data.tif DAPI --sigma 6,6,6  # Correct
limb clean-volume experiment data.tif DAPI --sigma 6 6 6  # Wrong

File Path Issues

# Use absolute paths
limb clean-volume /full/path/to/experiment /full/path/to/data.tif DAPI

# Check file permissions
ls -la data.tif

# Verify file exists
file data.tif

Quality Control

Poor Volume Processing Results

  • Check raw data quality: Ensure good signal-to-noise ratio
  • Adjust parameters: Try different sigma and cutoff values
  • Verify file format: Ensure TIFF files are not corrupted
  • Check memory: Large files may need more RAM

Surface Extraction Problems

  • Try automatic isovalue: Use --auto flag
  • Manual isovalue selection: Experiment with different values
  • Check volume quality: Poor input = poor surface
  • Consider manual cleaning: Use external tools if needed

Staging Failures

  • Place points correctly: Along proximal-distal axis AER
  • Use enough points: 10 points minimum recommended
  • Check surface quality: Poor surface affects staging

📋 FAQ (Frequently Asked Questions)

General Questions

Q: What file formats does LimbLab support? A: Input: TIFF volumes (.tif, .tiff). Output: VTK surfaces (.vtk), TIFF volumes, PNG images.

Q: How much memory do I need? A: Minimum 8GB, recommended 16GB+. Large volumes (>2GB) may need 32GB+.

Q: Can I process multiple channels at once? A: Not yet! Process each channel separately, then visualize together with limb vis isosurfaces experiment CHANNEL1 CHANNEL2.

Q: Is LimbLab free to use? A: Yes, LimbLab is open-source and free for academic and commercial use.

Technical Questions

Q: Why does my surface look noisy? A: Try adjusting the isovalue during surface extraction, or use the --auto flag for automatic selection.

Q: Can I automate the pipeline? A: Yes! Use Python scripts with the API, or create shell scripts for batch processing.

Q: What's the difference between linear and non-linear alignment? A: Linear: rotation/translation (faster). Non-linear: morphing (more accurate, slower).

Scientific Questions

Q: How accurate is the limb staging? A: Typically ±0.5 stages with good quality data. Accuracy depends on surface quality and point placement.

Q: Can I compare different developmental stages? A: Yes! Align each limb to the appropriate reference template for comparative limb.

Q: How do I quantify gene expression? A: Use the probe visualization tool to extract quantitative data from specific regions. More Gene Expression

Q: Can I analyze time series data? A: Yes! Process each time point separately, then compare aligned results.

Contributing

How to Help

  • Report bugs: Use GitHub Issues with detailed information
  • Suggest features: Describe your use case and requirements
  • Improve documentation: Submit pull requests for better docs
  • Share examples: Contribute to the examples repository
  • Answer questions: Help other users in discussions

Development

  • Code contributions: Fork the repository and submit pull requests
  • Testing: Help test new features and report issues
  • Documentation: Improve tutorials and user guides
  • Community: Participate in discussions and help new users

Contact Information

Primary Contact

  • Email: laura.avino@embl.es
  • Response time: Usually within 24-48 hours working hours
  • Best for: Technical support, bug reports, feature requests, say thanks!

Alternative Contacts

We're here to help! Don't hesitate to reach out if you need assistance with LimbLab. Our goal is to make 3D limb limb accessible to everyone.