Accounting for limited detection efficiency and localization precision in cluster analysis in single molecule localization microscopy
Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quanti...
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| Veröffentlicht in: | PloS one 2015-03, Vol.10 (3), p.e0118767-e0118767 |
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| creator | Shivanandan, Arun Unnikrishnan, Jayakrishnan Radenovic, Aleksandra |
| description | Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques' inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10-30 nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley's L(r) - r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization. |
| doi_str_mv | 10.1371/journal.pone.0118767 |
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However, such quantitative studies remain challenged by the techniques' inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10-30 nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley's L(r) - r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0118767</identifier><identifier>PMID: 25794150</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Analytical methods ; Audiovisual communications ; Bioengineering ; Biological effects ; Cell cycle ; Cluster Analysis ; Clusters ; Computer Simulation ; Correlation ; Efficiency ; Image Processing, Computer-Assisted ; Laboratories ; Limit of Detection ; Lipids ; Localization ; Membrane proteins ; Microscopy ; Microscopy - methods ; Normal distribution ; Photons ; Proteins ; Quantitative analysis ; Spatial discrimination ; Spatial resolution ; Studies</subject><ispartof>PloS one, 2015-03, Vol.10 (3), p.e0118767-e0118767</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Shivanandan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Shivanandan et al 2015 Shivanandan et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-d9eaf835ee1b27227d19ecaa49c5a48edc17a9e70174eb1b347f739405786c13</citedby><cites>FETCH-LOGICAL-c692t-d9eaf835ee1b27227d19ecaa49c5a48edc17a9e70174eb1b347f739405786c13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4368834/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4368834/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53770,53772,79347,79348</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25794150$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Hall, Adam R</contributor><creatorcontrib>Shivanandan, Arun</creatorcontrib><creatorcontrib>Unnikrishnan, Jayakrishnan</creatorcontrib><creatorcontrib>Radenovic, Aleksandra</creatorcontrib><title>Accounting for limited detection efficiency and localization precision in cluster analysis in single molecule localization microscopy</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques' inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10-30 nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley's L(r) - r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization.</description><subject>Accuracy</subject><subject>Analytical methods</subject><subject>Audiovisual communications</subject><subject>Bioengineering</subject><subject>Biological effects</subject><subject>Cell cycle</subject><subject>Cluster Analysis</subject><subject>Clusters</subject><subject>Computer Simulation</subject><subject>Correlation</subject><subject>Efficiency</subject><subject>Image Processing, Computer-Assisted</subject><subject>Laboratories</subject><subject>Limit of Detection</subject><subject>Lipids</subject><subject>Localization</subject><subject>Membrane proteins</subject><subject>Microscopy</subject><subject>Microscopy - methods</subject><subject>Normal 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sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques' inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10-30 nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley's L(r) - r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25794150</pmid><doi>10.1371/journal.pone.0118767</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Accuracy Analytical methods Audiovisual communications Bioengineering Biological effects Cell cycle Cluster Analysis Clusters Computer Simulation Correlation Efficiency Image Processing, Computer-Assisted Laboratories Limit of Detection Lipids Localization Membrane proteins Microscopy Microscopy - methods Normal distribution Photons Proteins Quantitative analysis Spatial discrimination Spatial resolution Studies |
| title | Accounting for limited detection efficiency and localization precision in cluster analysis in single molecule localization microscopy |
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