title: Visual representation of cell subpopulation from flow cytometry data.
abstract: Flow cytometric systems are useful for protein identification and expression analysis, especially characterizing particular lineage or sublineage of cells. We clustered flow cytometry data of bone marrow cells into subpopulations using a clustering algorithm with its physical characteristics (cell size and cell granularity) and different molecular composition (cell reactivity with monoclonal antibodies). To display the cell subpopulations, we created a colored map according to the mean of 5 flow cytometry parameters based on a cluster. Such a map can reveal subpopulation properties that are not evident in the widely used scatter plot.
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Eun Young
authors.initials: EY
authors.lastname: Kim
authors.forename: Qing T
authors.initials: QT
authors.lastname: Zeng
authors.forename: Frank C
authors.initials: FC
authors.lastname: Kuo
authors.forename: James
authors.initials: J
authors.lastname: Rawn
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Mentzer
mesh_terms: D000465:Algorithms; D001854:Bone Marrow Cells; D016000:Cluster Analysis; D003196:Computer Graphics; D005434:Flow Cytometry; D006801:Humans; D007938:Leukemia / Q000473:pathology; D016571:Neural Networks, Computer; D012984:Software