In life sciences, tracking objects from movies is pivotal for quantifying behaviors of particles, organelles, bacteria, cells, and whole animals. CellTracksColab bridges the gap between tracking and analysis. CellTracksColab simplifies the journey from data compilation to analysis.

---

🚀 Key Features

• 📘 Holistic View: Comprehensive analysis across fields of view, biological repeats, and conditions.
• 🖥️ User-Centric: Intuitive GUI designed for all users.
• 🔍 Visualization: Track visualization and filtering.
• 📊 Analysis: Deep-dive into track metrics and statistics.
• 🧪 Reliability: Check experimental variability using hierarchical clustering.
• 🔧 Advanced Tools: Harness the power of UMAP, t-SNE, and HDBSCAN.
• 💼 Flexibility: Tailor and adapt to your needs.

---

✅ Compatible with

TrackMate	CellProfiler	Icy	ilastik	Fiji Manual Tracker

May also be compatible with other tracking software exporting tracking results that meet our minimal requirements. More info here.

📹 Video Tutorials

Tutorial 1: Getting Started with CellTracksColab using Google Colab

Tutorial 2: Using CellTracksColab locally using Jupyter

Tutorial 3: Using CellTracksColab locally using Google Colab

🛠️ Quick Start

The easiest way to start using CellTracksColab is in the cloud using Google Collaboratory, but it can also be used on your own computer using Jupyter Notebooks. See our wiki for installation instructions.

1. Load and Plot Your Data

We provide three notebooks for loading and analyzing your data depending on its format:

Notebook	Purpose	Required File Format	Link
CellTracksColab - TrackMate	Load and analyze TrackMate data. More info here.	CSV or XML files
CellTracksColab - Custom	Analyze data from CellProfiler, ICY, ilastik, or Fiji Manual Tracker. More info here.	CSV files
CellTracksColab - Viewer	Load and share data in the CellTracksColab format.	CellTracksColab format

2. Advanced Analysis Modules

These notebooks require your dataset to be in the CellTracksColab format.

Notebook	Purpose	Required File Format	Link
CellTracksColab - Dimensionality Reduction	Utilize advanced dimensionality reduction techniques.	CellTracksColab format
CellTracksColab - Track Spatial Clustering Analysis	Dive deeper into your dataset with track clustering analysis.	CellTracksColab format
CellTracksColab - Distance to ROI	Analyze movement tracks in relation to designated ROIs.	CellTracksColab format

More to come

Other Notebooks

CellTracksColab - TrackMate - Plate:

• Handle TrackMate CSV files structured in a plate format, such as file names commonly produced by incubator microscopes like Incucytes.
• 

---

⭐️ Acknowledgments

CellTracksColab is inspired by several key projects in cell tracking and analysis. We acknowledge the influential contributions of Traject3d, CellPhe, CelltrackR, the MotilityLab website, and Cellplato on Zenodo. The innovative use of UMAP and HDBSCAN for analyzing tracking data, as featured in CellTracksColab, was first introduced in CellPlato.

---

📦 Resources

• Test Dataset: Start exploring with our test datasets in CellTracksColab CSV format, or TrackMate CSV format.
• Data Structure: Organize with our two-tiered folder hierarchy. Details here.
• Data Requirements: Note that CellTracksColab does not yet support track merging or splitting.

---

📚 Documentation

Dive deeper. Visit our comprehensive wiki.

---

✍️ Contributors

• Estibaliz Gómez-de-Mariscal
• Hanna Grobe
• Joanna W. Pylvänäinen
• Laura Xénard
• Ricardo Henriques
• Jean-Yves Tinevez
• Guillaume Jacquemet

---

🤝 Contribute

We welcome your insights and improvements! There are several ways you can contribute to the CellTracksColab project:

Issues

If you encounter any bugs, have suggestions for improvements, or want to discuss new features, please raise an issue on our GitHub Issues page.

New Analysis Notebooks

We are excited to see new analysis notebooks built on the CellTracksColab platform. If you have developed a new notebook, please submit it via a pull request. All submitted notebooks should include a test dataset to showcase their functionality. Each notebook will be tested by a member of the team before being released.

Code of Conduct

We expect all contributors to adhere to our simple code of conduct:

• Be respectful and considerate of others.
• Provide constructive feedback.
• Collaborate openly and honestly.

By participating in this project, you agree to abide by these guidelines.

---

Thank you for contributing to CellTracksColab! Your support and contributions help us improve and expand the platform for everyone in the community.

---

License

Licensed under the MIT License. Details here.

---

📜 Citation

If you use CellTracksColab in your research, please cite the following paper:

Reference

Gómez-de-Mariscal, E., Grobe, H., Pylvänäinen, J. W., Xénard, L., Henriques, R., Tinevez, J.-Y., & Jacquemet, G. (2024). CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data. PLOS Biology. Published August 8, 2024. https://doi.org/10.1371/journal.pbio.3002740

🖼️ Screenshots

Figure 1: Compile your data	Figure 2: Visualise your tracks
Figure 3: Compute additional metrics	Figure 4: Plot track parameters
Figure 5: Compute Similarity Metrics between Field of Views and between Conditions and Repeats	Figure 6: Perform UMAP
Figure 7: Identify clusters using HDBSCAN	Figure 8: Understand your clusters using a heatmap

---