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Zone Equalisation Normalisation

Zone Equilisation Normalisation (ZEN) is a method for normalising genomic signal bigWigs, such as ATAC-seq, ChIP-seq and TT-seq. ZEN is avaliable within the Python package ZEN-norm, which also includes modules for reversing prior bigWig normalisation and creating plots to compare performance of normalisation methods genome-wide.

Citation: T. Wilson, TA. Milne, SG. Riva and JR. Hughes, Zone Equalisation Normalisation For Improved Alignment of Epigenetic Signal, bioRvix, 2025



Contents
  1. Installation
  2. Tutorials


1. Installation

ZEN-norm is designed to run on Python 3.10 and above. It is installable from either Conda (recommended) or PyPI.

Conda Installation To install the ZEN-norm package from Conda, active the conda environment you'd like to install the package into (conda activate [environment_name]) and run the command below:
conda install tommakesthings::zen-norm

Or alternatively:

conda install -c https://conda.anaconda.org/TomMakesThings zen-norm

If there are issues running either of the above, a conda environment with the required packages can be created with the zen_environment.yml file.

conda env create --name zen_env --file=environment/zen_environment.yml
conda activate zen_env

PyPI Installation To install the ZEN-norm package from PyPI, run the command below:
pip install ZEN-norm

Some ZEN-norm features require samtools, which is not distributed via PyPI and must be installed separately.



2. Tutorials

See the Tutorials page on GitHub for explanations of how to use ZEN-norm to:

  • Normalise bigWigs with ZEN
  • Reverse prior bigWig normalisation
  • Compare and quanity normalisation method genome-wide alignment via Wasserstein distance
  • Create plots included in the publication

Metadata

Release files for ZEN-norm 1.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for ZEN-norm 1.0.2
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Table of built distributions (wheels) for ZEN-norm 1.0.2
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