title: Multifactorial comparative study of spatial point pattern analysis methods.
abstract: 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, Voronoï 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.
authors.affiliation: Laboratoire de Cancérologie Expérimentale, CJF INSERM 9311, IFR Jean Roche, Faculté de Médecine Nord, Boulevard Pierre Dramard, Marseille Cedex 20, 13916, France.
authors.forename: F
authors.initials: F
authors.lastname: Wallet
authors.forename: C
authors.initials: C
authors.lastname: Dussert
mesh_terms: D000818:Animals; D002477:Cells / Q000648:ultrastructure; D003198:Computer Simulation; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000648:ultrastructure