Abstract
There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells.
Highlights
The eukaryotic cell nucleus is a membrane-bound organelle that performs vital functions in regulating, translating and replicating the cell’s genome
Problems Associated with Spatial Point Pattern Analysis we provide an overview of quantitative reasoning about nuclear architecture and the difficulties that can arise
Dataset Description The following experiments are designed to highlight difficulties in applying spatial point pattern analysis tools to determine whether there is interesting spatial preference, especially in the case of patterns generated by compartments that manifest few objects per nucleus
Summary
The eukaryotic cell nucleus is a membrane-bound organelle that performs vital functions in regulating, translating and replicating the cell’s genome. The nucleus contains distinct structures comprising assemblies of macromolecular complexes referred to as nuclear compartments [1] Examples of such compartments include splicing speckles, chromosome territories, nucleoli and PML nuclear bodies [2]. A typical approach for exploring the spatial preference of compartments involves an exploratory spatial hypothesis test to determine if the observed point pattern is consistent with the simplest spatial model: complete spatial randomness (CSR), that is, a homogeneous spatial Poisson process. This is not an interesting model – corresponding to a compartment that has no spatial preference and no selfinteractions. The concern of this paper is to demonstrate that standard data analysis approaches for exploring spatial preference, for compartments which manifest as few objects per nucleus, are prone to overlook interesting preferences
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