The Challenge of Clustering Flow Cytometry Data from Phytoplankton in Lakes

; ; ; ; (). The Challenge of Clustering Flow Cytometry Data from Phytoplankton in Lakes. CCIS, 438 379 - 386. Peer reviewed.

ClusteringFlow cytometry (FC) devices count and measure cells in fluids
in an automated procedure. In this paper we present our work in
progress on the clustering of FC data. We compare standard clustering
algorithms such as K-means, Ward’s clustering, etc., to the more advanced
approach of sequential superparamagnetic clustering (SSC). We
found Ward’s hierarchical clustering to perform best regarding internal
cluster validation measures, while SSC yielded the best results based on
the visual inspection of the clustering results.