sk-cyto - Flow cytometry algorithms for scikit-learn

sk-cyto brings flow cytometry to scikit-learn.

Flow cytometry is extremely amenable to regular machine learning algorithms. At the same time, it requires specific data transformations, and various dedicated analysis methods have been developed. sk-cyto allows you to combine the best of sk-learn infrastructure with dedicated cytometry analysis methods. Use established patterns, such as Pipeline and existing Transformers together with state-of-the-art algorithms like FlowSOM.

Refer to the documentation for a full list of available Transformers and Estimators

This package is work in progress. New features and algorithms will be implemented frequently.

Installation

From PyPI:

pip install sk-cyto

Install from Github source code with:

git clone git@github.com:MSHelm/sk-cyto.git
cd sk-cyto
pip install .