CytoNormPy

CytoNormPy implements the CytoNorm algorithm in Python for removing batch effects in cytometry datasets.

Key Features:

• Speed Improvement: Runs up to 85% faster than the R implementation of CytoNorm.
• Python Compatibility: Fully compatible with common single-cell data structures and frameworks of Python.
• Complete Feature Set: Implements the complete feature set of CytoNorm 2.0.
• Clustering Algorithms: Extends previous functionality by adding common clustering algorithms.
• Visualizations: Provides key visualizations of the algorithm and its evaluation.

Scientific Applications:

• Clinical Diagnostics: Enables batch effect removal in cytometry data used for clinical diagnostics.
• Clinical Studies: Supports batch effect correction in cytometry data from clinical studies.
• Fundamental Research: Facilitates analysis of cytometry data in research settings by accounting for technical variation.

Methodology:

The implementation is based on the CytoNorm algorithm for batch effect removal in cytometry datasets.