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

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.

Keywords

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