MSIght
======

MSIght is a powerful and flexible tool for integrating multispectral imaging data with histological analysis and proteomics-based insights. It is designed to streamline your data workflows, from pre-processing and registration to clustering and visualization.

Installation
------------

You can install MSIght from PyPI with:

.. code-block:: console

   pip install MSIght

If you prefer to install from source, clone the GitHub repository and run:

.. code-block:: console

   git clone https://github.com/lingjunli-research/MSIght.git
   cd MSIght
   pip install .


A Quick Example
---------------

Here's a quick example showing how to load data, apply an analysis pipeline, and visualize the results:

.. code-block:: python

   from MSIght.refactor_segment import cluster_msi
   from MSIght import refactor_common_functions

   filename = "my_data.imzML"
   output_directory = "results"
   sample_name = "sample_001"
   sigma = 1.0
   structuring_element_size = 3
   pca_components = 2
   tsne_components = 2
   tsne_perplexity = 30
   tsne_learning_rate = 200
   tsne_iterations = 500
   k_means_cluster_number = 5

   # Run the clustering pipeline
   results = cluster_msi(filename, output_directory, sample_name, sigma, structuring_element_size,
                         pca_components, tsne_components, tsne_perplexity,
                         tsne_learning_rate, tsne_iterations, k_means_cluster_number)

   # The returned 'results' can now be used for further analysis or visualization
   # For example, you can use refactor_common_functions to process or plot your data

Documentation
-------------

For more detailed usage guides, tutorials, and API references, please see the following pages:

- :doc:`modules`
- :doc:`api_reference`

These pages provide comprehensive details on each module, as well as code examples, parameters, and return values for all public functions.

Contributing
------------

We welcome contributions! If you want to report a bug, suggest a feature, or contribute code:

1. Check the issue tracker for existing reports or requests.
2. Submit a new issue if your topic isn't covered.
3. Fork the repository, make your changes, and open a pull request.

Your feedback and involvement help improve MSIght for everyone.