Analyzing high-dimensional cytometry data using FlowSOM

Katrien Quintelier, Artuur Couckuyt, Annelies Emmaneel, Joachim Aerts, Yvan Saeys, Sofie Van Gassen

Published: 2021-06-24 DOI: 10.1038/s41596-021-00550-0

FlowSOM

Cytometry Data Analysis

High-Dimensional Data

Unsupervised Clustering

R Protocol

AI 解读

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Data integration（数据集成）

Heterogeneity（异质性）

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The dimensionality of cytometry data has strongly increased in the last decade, and in many situations the traditional manual downstream analysis becomes insufficient. The field is therefore slowly moving toward more automated approaches, and in this pape
Introduction
Materials
Procedure
Troubleshooting
Timing
Anticipated results
References
ACKNOWLEDGMENTS
ACKNOWLEDGMENTS

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Analyzing high-dimensional cytometry data using FlowSOM

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