☆ 4.3 Article

Detection and monitoring of normal and leukemic cell populations with hierarchical clustering of flow cytometry data

CYTOMETRY PART A (2012)

Journal

CYTOMETRY PART A

Volume 81A, Issue 1, Pages 25-34

Publisher

WILEY

DOI: 10.1002/cyto.a.21148

Keywords

hierarchical clustering; minimal residual disease; acute lymphoblastic leukemia; support vector machines; multiparameter flow cytometry

Categories

Biochemical Research Methods Cell Biology

Funding

JGW Patterson Foundation, UK [BH070348]
Czech Ministry of Education [MSM0021620813]

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Abstract

Flow cytometry is a valuable tool in research and diagnostics including minimal residual disease (MRD) monitoring of hematologic malignancies. However, its gradual advancement toward increasing numbers of fluorescent parameters leads to information rich datasets, which are challenging to analyze by standard gating and do not reflect the multidimensionality of the data.

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