The future of flow cytometry data analysis: Navigating a new world with algorithms and machine learning
In this perspective, ICON details their semi-automated analysis and advanced R-based pipelines, integrating algorithms like PeacoQC, FlowSOM and UMAP to optimize high-parameter flow cytometry analysis. Explore the full article to learn more about how this approach streamlines workflows, improves scalability and ensures consistent results, enabling professionals to gain deeper insights into high-dimensional datasets.
The future of flow cytometry data analysis_A CRO perspective
This feature is part of the Bioanalysis Zone Spotlight on flow cytometry in bioanalysis. For more expert opinions on this topic, visit our feature homepage.
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