Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy
Document Type
Article
Publication Date
6-21-2017
Keywords
Cluster analysis, Clustering Density
Abstract
We report a robust nonparametric descriptor, J'(r), for quantifying the density of clustering molecules in single-molecule localization microscopy. J'(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that J'(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. Most importantly, the position of the J'(r) valley ([Formula: see text]) depends exclusively on the density of clustering molecules (ρc). Therefore, it is ideal for direct estimation of the clustering density of molecules in single-molecule localization microscopy. As an example, this descriptor was applied to estimate the clustering density of ptsG mRNA in E. coli bacteria.
Citation
Jiang, S., Park, S., Challapalli, S. D., Fei, J., & Wang, Y. (2017). Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. Physics Faculty Publications and Presentations., 12 (6) https://doi.org/https://doi.org/10.1371/journal.pone.0179975
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