Artuur Couckuyt, Benjamin Rombaut, Yvan Saeys, S. van Gassen
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引用次数: 0
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
The FlowSOM Python implementation is freely available on GitHub: https://github.com/saeyslab/FlowSOM_Python.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
MOTIVATION We describe a new Python implementation of FlowSOM, a clustering method for cytometry data.ResultThis 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.AVAILABILITYThe FlowSOM Python implementation is free available on GitHub: https://github.com/saeyslab/FlowSOM_Python.SUPPLEMENTARY INFORMATIONSupplementary data are available at Bioinformatics online.
期刊介绍：
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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