Evaluation of flow cytometry automated data analysis platform performance for rare event detection
conference contributionposted on 29.06.2020 by Melissa Cheung, Jonathan Campbell, Julian Braybrook, Rob Thomas, Jon Petzing
Any type of content contributed to an academic conference, such as papers, presentations, lectures or proceedings.
Flow cytometry is a widely used technique for the detection and quantification of low frequency or rare cell populations at limits of detection (LOD) of 0.1% or lower, such as circulating tumour cells and haematopoietic stem cells. An increasing number of computational tools are available for automated gating of flow cytometry data. These tools have the capability to eliminate operator variation from traditional manual gating. Nevertheless, the potential for variation in data outputs arising from analysis of the same dataset using different algorithms means that research is needed to define the confidence in the use of automated data analysis software platforms for identifying rare cell populations.
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