Abstract
Flow cytometry is an appropriate technique for the investigation and monitoring of phytoplankton (algae), providing quick, semi-automatic single-cell analysis. However, to use flow cytometry in phytoplankton research routinely, an objective and automated i.e. computer-supported data analysis is demanded. For this reason, in a pilot study a sequence of different steps of cluster analysis has been developed, including model-based and hierarchical clustering, as well as the concept of cores and weighting of observations and parameters. A successful application of the method is demonstrated for a snapshot of a sample of Lake Müggelsee in Berlin (Germany).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BODDY, L., MORRIS, C.W., WILKINS, M.F., AL-HADDAD, L., TARRAN, G.A., JONKER, R.R., and BURKILL, P.H. (2000): Identification of 72 phytoplankton species by radial basis function neural network analysis of flow cytometric data. Marine Ecology Progress Series, 195, 47–59.
CHISOLM, S.W, OLSON, R.J, ZETTLER, E.R., GOERICKE, R., WATER-BURY, J.B., and WELSHMEYER, N.A. (1988): A novel free-living prochlorophyte abundant in the oceanic euphotic zone. Nature, 334, 340–343.
FRALEY, C. and RAFTERY, A.E. (2002): Model-based Clustering, Discriminant Analysis, and Density Estimation. Journal, of the American Statistical Association, 97, 458, 611–631.
HOFSTRAAT, J.W., ZEIJL VAN, W.J.M., VREEZE DE, M.E.J., PEETERS, J.C.H., PEPERZAK, L., COLIJN, F., and RADEMAKER, T.W.M. (1994): Phytoplankton monitoring by flow cytometry. Journal of Plankton Research 16(9), 1197–1224.
MACQUEEN, J.B. (1967): Some Methods for Classification and Analysis of Multi-variate Observations. In: L. Lecam and J. Neyman (Eds.): Proc. 5th Berkeley Symp. Math. Statist. Prob., Vol. 1. Univ. California Press, Berkeley, 281–297.
MUCHA, H.-J, SIMON, U, and BRÜGGEMANN, R. (2002): Model-based Cluster Analysis Applied to Flow Cytometry Data of Phytoplankton. Weierstraß-Institute for Applied Analysis and Stochastic, Technical Report No. 5. http://www.wias-berlin.de/.
STEINBERG, C.E.W. and BRÜGGEMANN, R. (1998): Integrity of limnic ecosystems. In: J.A. Van de Kraats (Eds.): Let the Fish Speak: The Quality of Aquatic Ecosystems as an Indicator for Sustainable Water Management. EURAQUA: Fourth Technical Report, Koblenz, 89–101.
WARD, J.H. (1963): Hierarchical Grouping Methods to Optimise an Objective Function. JASA, 58, 235–244.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
Simon, U., Mucha, HJ., Brüggemann, R. (2005). Model-Based Cluster Analysis Applied to Flow Cytometry Data. In: Baier, D., Wernecke, KD. (eds) Innovations in Classification, Data Science, and Information Systems. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26981-9_9
Download citation
DOI: https://doi.org/10.1007/3-540-26981-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23221-6
Online ISBN: 978-3-540-26981-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)