Tutorials
=========

.. toctree::
   :maxdepth: 2
   :hidden:

   deepstarr_local

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 <https://colab.research.google.com/drive/1HOM_ysa4HIh_ZoYzLwa4jZu4evyRntF7?usp=sharing>`_

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 <https://raw.githubusercontent.com/evanseitz/seam-nn/main/examples/example_deepstarr_local_20647_intgrad.py>`_

Step-by-Step Guide
~~~~~~~~~~~~~~~~
For a more detailed explanation of each step, see our :doc:`step-by-step guide <deepstarr_local>`.

Additional Resources
------------------

For more examples and use cases, visit our `GitHub repository <https://github.com/evanseitz/seam-nn>`_.

.. note::
   Updates and additional content will be added in future releases.