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Systematic and general method for quantifying localization in microscopy images
Quantifying the localization of molecules with respect to other molecules, cell structures and intracellular regions is essential to understanding their regulation and actions. However, measuring localization from microscopy images is often difficult with existing metrics. Here, we evaluate a metric...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Company of Biologists Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5200903/ https://www.ncbi.nlm.nih.gov/pubmed/27979831 http://dx.doi.org/10.1242/bio.019893 |
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author | Sheng, Huanjie Stauffer, Weston Lim, Han N. |
author_facet | Sheng, Huanjie Stauffer, Weston Lim, Han N. |
author_sort | Sheng, Huanjie |
collection | PubMed |
description | Quantifying the localization of molecules with respect to other molecules, cell structures and intracellular regions is essential to understanding their regulation and actions. However, measuring localization from microscopy images is often difficult with existing metrics. Here, we evaluate a metric for quantifying localization termed the threshold overlap score (TOS), and show it is simple to calculate, easy to interpret, able to be used to systematically characterize localization patterns, and generally applicable. TOS is calculated by: (i) measuring the overlap of pixels that are above the intensity thresholds for two signals; (ii) determining whether the overlap is more, less, or the same as expected by chance, i.e. colocalization, anti-colocalization, or non-colocalization; and (iii) rescaling to allow comparison at different thresholds. The above is repeated at multiple threshold combinations to generate a TOS matrix to systematically characterize the relationship between localization and signal intensities. TOS matrices were used to identify and distinguish localization patterns of different proteins in various simulations, cell types and organisms with greater specificity and sensitivity than common metrics. For all the above reasons, TOS is an excellent first line metric, particularly for cells with mixed localization patterns. |
format | Online Article Text |
id | pubmed-5200903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | The Company of Biologists Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-52009032017-01-13 Systematic and general method for quantifying localization in microscopy images Sheng, Huanjie Stauffer, Weston Lim, Han N. Biol Open Methods & Techniques Quantifying the localization of molecules with respect to other molecules, cell structures and intracellular regions is essential to understanding their regulation and actions. However, measuring localization from microscopy images is often difficult with existing metrics. Here, we evaluate a metric for quantifying localization termed the threshold overlap score (TOS), and show it is simple to calculate, easy to interpret, able to be used to systematically characterize localization patterns, and generally applicable. TOS is calculated by: (i) measuring the overlap of pixels that are above the intensity thresholds for two signals; (ii) determining whether the overlap is more, less, or the same as expected by chance, i.e. colocalization, anti-colocalization, or non-colocalization; and (iii) rescaling to allow comparison at different thresholds. The above is repeated at multiple threshold combinations to generate a TOS matrix to systematically characterize the relationship between localization and signal intensities. TOS matrices were used to identify and distinguish localization patterns of different proteins in various simulations, cell types and organisms with greater specificity and sensitivity than common metrics. For all the above reasons, TOS is an excellent first line metric, particularly for cells with mixed localization patterns. The Company of Biologists Ltd 2016-12-09 /pmc/articles/PMC5200903/ /pubmed/27979831 http://dx.doi.org/10.1242/bio.019893 Text en © 2016. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by/3.0This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Methods & Techniques Sheng, Huanjie Stauffer, Weston Lim, Han N. Systematic and general method for quantifying localization in microscopy images |
title | Systematic and general method for quantifying localization in microscopy images |
title_full | Systematic and general method for quantifying localization in microscopy images |
title_fullStr | Systematic and general method for quantifying localization in microscopy images |
title_full_unstemmed | Systematic and general method for quantifying localization in microscopy images |
title_short | Systematic and general method for quantifying localization in microscopy images |
title_sort | systematic and general method for quantifying localization in microscopy images |
topic | Methods & Techniques |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5200903/ https://www.ncbi.nlm.nih.gov/pubmed/27979831 http://dx.doi.org/10.1242/bio.019893 |
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