AI Article Synopsis
- A new Python implementation of FlowSOM, a clustering method for analyzing cytometry data, has been developed.
- This version is quicker than the original in R and is designed to efficiently handle single-cell omics data, while retaining all original visualizations like star and pie plots.
- You can access the FlowSOM Python implementation for free on GitHub at: https://github.com/saeyslab/FlowSOM_Python.
Article Abstract
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.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11052654 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/btae179 | DOI Listing |
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