Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy.
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...
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Public Library of Science (PLoS)
2017-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5479598?pdf=render |
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author | Shenghang Jiang Seongjin Park Sai Divya Challapalli Jingyi Fei Yong Wang |
author_facet | Shenghang Jiang Seongjin Park Sai Divya Challapalli Jingyi Fei Yong Wang |
author_sort | Shenghang Jiang |
collection | DOAJ |
description | 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. |
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institution | Directory Open Access Journal |
issn | 1932-6203 |
language | English |
last_indexed | 2024-12-20T08:44:10Z |
publishDate | 2017-01-01 |
publisher | Public Library of Science (PLoS) |
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spelling | doaj.art-dda2946d59324adaa189ea383462457e2022-12-21T19:46:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01126e017997510.1371/journal.pone.0179975Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy.Shenghang JiangSeongjin ParkSai Divya ChallapalliJingyi FeiYong WangWe 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.http://europepmc.org/articles/PMC5479598?pdf=render |
spellingShingle | Shenghang Jiang Seongjin Park Sai Divya Challapalli Jingyi Fei Yong Wang Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. PLoS ONE |
title | Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. |
title_full | Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. |
title_fullStr | Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. |
title_full_unstemmed | Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. |
title_short | Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy. |
title_sort | robust nonparametric quantification of clustering density of molecules in single molecule localization microscopy |
url | http://europepmc.org/articles/PMC5479598?pdf=render |
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