Multifactorial Comparative Study of Spatial Point Pattern Analysis Methods

A way of studying cooperative behaviour of biological entities (proteins, cells, etc.) is by using topographical analysis: the quantification of the spatial patterns formed by the entities considered as points. Five methods of topographical analysis were compared in terms of discriminant power, stab...

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Bibliographic Details
Published in:Journal of theoretical biology 1997-08, Vol.187 (3), p.437-447
Main Authors: Wallet, France, Dussert, Christophe
Format: Article
Language:English
Subjects:
Animals
Cells - ultrastructure
Computer Simulation
Models, Biological
Models, Statistical
Neoplasms - ultrastructure
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Summary:A way of studying cooperative behaviour of biological entities (proteins, cells, etc.) is by using topographical analysis: the quantification of the spatial patterns formed by the entities considered as points. Five methods of topographical analysis were compared in terms of discriminant power, stability of parameters, methodological bias and algorithms. We tested five methods (nearest neighbour distribution, radial distribution, Voronoı̈ paving, quadrat count, minimal spanning tree graph) which generated nine parameters on four simulated models (random point process, hardcore model and two cluster models) and on experimental cellular models. The method which offers the best discrimination power and stability seems to be the minimal spanning tree graph edge length distribution.
ISSN:0022-5193
1095-8541
DOI:10.1006/jtbi.1997.0445