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Welcome to PENGUIN's documentation!
===================================

**PENGUIN** - Percentile Normalization GUI Image deNoising is a rapid and efficient image preprocessing pipeline for multiplexed spatial proteomics. In comparison to existing approaches, PENGUIN stands out by eliminating the need for manual annotation or machine learning model training. It effectively preserves signal intensity differences and reduces noise.

PENGUIN's simplicity, speed, and user-friendly interface, deployed both as script and as a Jupyter notebook, facilitate parameter testing and image processing.

This repository contains the documentation files for running PENGUIN.

The general view of PENGUIN:

.. image:: ../../figs/main_figure.png


.. toctree::
   :maxdepth: 2
   :caption: Contents:

   usage
   notebook_usage
   script_usage
   functions_usage

Credits
==========
If you find this repository useful in your research or for educational purposes please refer to:

License
==========

Developed at the Leiden University Medical Centre, The Netherlands and
Centre of Biological Engineering, University of Minho, Portugal

Released under the GNU Public License (version 3.0).



Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`