Efficient cytometry analysis with FlowSOM in Python boosts interoperability with other single-cell tools
Artuur Couckuyt1,2, Benjamin Rombaut1,2, Yvan Saeys1,2
1Department of Applied Mathematics, Computer Science and Statistics, Ghent University, 9000 Ghent, Belgium.
Motivation:
We describe a new Python implementation of FlowSOM, a clustering method for cytometry data.
Results:
This implementation is faster than the original version in R, better adapted to work with single-cell omics data including integration with current single-cell data structures and includes all the original visualizations, such as the star and pie plot.
Availability And Implementation:
The FlowSOM Python implementation is freely available on GitHub: https://github.com/saeyslab/FlowSOM_Python.
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