Tutorials

Overview

SEAM provides a comprehensive framework for analyzing regulatory mechanisms using deep learning models. Our tutorials demonstrate how to:

  • Preprocess data and load models

  • Construct in silico mutagenesis libraries

  • Generate attribution maps

  • Perform mechanism clustering and visualization

  • Generate and interpret MSMs (Mechanism Summary Matrices)

  • Identify and visualize key mechanisms

Available Tutorials

Interactive Tutorial

For a hands-on introduction to SEAM, we recommend starting with our interactive Google Colab tutorial. This notebook provides a complete walkthrough using the DeepSTARR model to analyze local regulatory mechanisms:

Launch Interactive Tutorial

Local Python Script

For users who prefer to run analyses locally or need to process large datasets, we provide a Python script version of the tutorial:

Download Python Script

Step-by-Step Guide

For a more detailed explanation of each step, see our step-by-step guide.

Additional Resources

For more examples and use cases, visit our GitHub repository.

Note

Updates and additional content will be added in future releases.