Abstract
Motivation We present a python implementation of the widely used CytoNorm algorithm for the removal of batch effects.
Results Our implementation ran up to 85% faster than its R counterpart, while being fully compatible with common single-cell data structures and -frameworks of python. We extend the previous functionality by adding common clustering algorithms and provide key visualizations of the algorithm and its evaluation.
Availability and implementation The CytoNormPy implementation is freely available on GitHub: https://github.com/TarikExner/CytoNormPy.
Competing Interest Statement
The authors have declared no competing interest.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Posted July 22, 2024.
CytoNormPy enables a fast and scalable removal of batch effects in cytometry datasets
