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：
The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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