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:

Contents:

• Set up
  • Installation
  • Environment set up
• Notebook usage
• Script usage
• Functions usage
  • Parse Image
  • Preprocessing Image
  • Thresholding
  • Percentile Filter
  • Save Images

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

• Index

• Module Index

• Search Page