Unité d'Analyse d'Images Quantitative, Institut Pasteur, Paris, France ; Unité de Recherche Associée 2582, Centre National de la Recherche Scientifique, Paris, France.
Unité Mixte de Recherche 518 Mathématiques et Informatique Appliquées, AgroParisTech and INRA, Paris, France.
PLoS One. 2013 Dec 4;8(12):e80914. doi: 10.1371/journal.pone.0080914. eCollection 2013.
One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules' interactions and physical interplay with their environment. The standard tool for analyzing molecules' distribution statistically is the Ripley's K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles' computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters' size from the maxima of the Ripley's K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of 2 μm, which suggests distinct physical mechanisms and cellular functions for each pathway.
分子生物学中的一个主要问题是观察到的分子的空间分布是随机的还是以簇的形式组织的。事实上,这种分析提供了关于分子相互作用及其与环境物理相互作用的信息。分析分子分布的标准统计工具是 Ripley 的 K 函数,它通过计算其临界分位数来测试空间随机性。然而,分位数的计算非常繁琐,阻碍了它的使用。在这里,我们提出了这些分位数的解析表达式,得到了一个快速而稳健的统计检验,并从 Ripley 的 K 函数的最大值中推导出特征簇的大小。随后,我们分析了细胞膜内吞斑的空间组织,报告说网格蛋白斑是随机分布的,而网格蛋白非依赖性斑则以 2μm 的半径聚集在一起,这表明每个途径都有不同的物理机制和细胞功能。