An optimal transport-based low-dimensional visualization framework for high-parameter flow cytometry

Abstract excerpt

Conventional data visualization techniques in single-cell analysis (such as two-dimensional dot plots, SPADE, PCA, t-SNE, or UMAP) often fall short in providing an intuitive understanding of high-parameter flow cytometry data. These methods tend to oversimplify complex biological relationships, lack biologically meaningful interpretations, and offer no principled framework for downstream quantitative analysis. To...

Topics

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• Algorithms
• Biomarkers
• Cluster Analysis
• Computer Graphics
• Flow Cytometry
• Immunophenotyping
• Mass Spectrometry
• Phenotype

Identifiers and source

Literature Corpus work

1db113b2-cb1f-50aa-aedc-24978ebe869f

DOI

10.1101/2025.08.19.670604