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Using FLOOD, a new multidimensional analysis method for flow cytometry data, to identify different cell subsets in disease

Tuesday 9 August 2016

Flow cytometry is a technique used for analysis of expression markers of single cells. It is widely used within the clinic for diagnosing disease and in research to understand the pathology of disease and to identify different cell subsets. During the last decennium, flow cytometers have been equipped with more lasers, enabling measurements of up to 17 parameters per cell. Analyzing these data still occurs by manual gating in two dimensional plots, which is time consuming and could leave potential correlations undiscovered. In collaboration with the group of Jeroen Jansen at the Radboud University we developed a method to analyze flow cytometry data in a multi-dimensional disease specific space: FLow cytometric Orthogonal Orientation for Diagnosis (FLOOD). The use of FLOOD enables researchers to identify disease-specific cells in an unsupervised multi-dimensional way. We will collect data of HIV patients and lung cancer patients to compare neutrophil subsets of these patients with neutrophil subsets found after LPS infusion. Additionally, we analyze expression markers on bone marrow cells of leukemia patients using FLOOD, enabling us to identify and characterize tumor clones.

Techniques:
White blood cell isolation; cell culture; flow cytometry; microscopy

Duration:
6-9 months

Contact:
Dr. Nienke Vrisekoop N.Vrisekoop@umcutrecht.nl
Prof. Dr. Leo Koenderman L.Koenderman@umcutrecht.nl