A global sampler of single particle tracking solutions for single molecule microscopy.

The dependence on model-fitting to evaluate particle trajectories makes it difficult for single particle tracking (SPT) to resolve the heterogeneous molecular motions typical of cells. We present here a global spatiotemporal sampler for SPT solutions using a Metropolis-Hastings algorithm. The sample...

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Main Authors: Michael Hirsch, Richard Wareham, Ji W Yoon, Daniel J Rolfe, Laura C Zanetti-Domingues, Michael P Hobson, Peter J Parker, Marisa L Martin-Fernandez, Sumeetpal S Singh
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0221865
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spelling doaj-954a80e8d52c435d894c61e32f26ef772021-03-03T21:05:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011410e022186510.1371/journal.pone.0221865A global sampler of single particle tracking solutions for single molecule microscopy.Michael HirschRichard WarehamJi W YoonDaniel J RolfeLaura C Zanetti-DominguesMichael P HobsonPeter J ParkerMarisa L Martin-FernandezSumeetpal S SinghThe dependence on model-fitting to evaluate particle trajectories makes it difficult for single particle tracking (SPT) to resolve the heterogeneous molecular motions typical of cells. We present here a global spatiotemporal sampler for SPT solutions using a Metropolis-Hastings algorithm. The sampler does not find just the most likely solution but also assesses its likelihood and presents alternative solutions. This enables the estimation of the tracking error. Furthermore the algorithm samples the parameters that govern the tracking process and therefore does not require any tweaking by the user. We demonstrate the algorithm on synthetic and single molecule data sets. Metrics for the comparison of SPT are generalised to be applied to a SPT sampler. We illustrate using the example of the diffusion coefficient how the distribution of the tracking solutions can be propagated into a distribution of derived quantities. We also discuss the major challenges that are posed by the realisation of a SPT sampler.https://doi.org/10.1371/journal.pone.0221865
collection DOAJ
language English
format Article
sources DOAJ
author Michael Hirsch
Richard Wareham
Ji W Yoon
Daniel J Rolfe
Laura C Zanetti-Domingues
Michael P Hobson
Peter J Parker
Marisa L Martin-Fernandez
Sumeetpal S Singh
spellingShingle Michael Hirsch
Richard Wareham
Ji W Yoon
Daniel J Rolfe
Laura C Zanetti-Domingues
Michael P Hobson
Peter J Parker
Marisa L Martin-Fernandez
Sumeetpal S Singh
A global sampler of single particle tracking solutions for single molecule microscopy.
PLoS ONE
author_facet Michael Hirsch
Richard Wareham
Ji W Yoon
Daniel J Rolfe
Laura C Zanetti-Domingues
Michael P Hobson
Peter J Parker
Marisa L Martin-Fernandez
Sumeetpal S Singh
author_sort Michael Hirsch
title A global sampler of single particle tracking solutions for single molecule microscopy.
title_short A global sampler of single particle tracking solutions for single molecule microscopy.
title_full A global sampler of single particle tracking solutions for single molecule microscopy.
title_fullStr A global sampler of single particle tracking solutions for single molecule microscopy.
title_full_unstemmed A global sampler of single particle tracking solutions for single molecule microscopy.
title_sort global sampler of single particle tracking solutions for single molecule microscopy.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description The dependence on model-fitting to evaluate particle trajectories makes it difficult for single particle tracking (SPT) to resolve the heterogeneous molecular motions typical of cells. We present here a global spatiotemporal sampler for SPT solutions using a Metropolis-Hastings algorithm. The sampler does not find just the most likely solution but also assesses its likelihood and presents alternative solutions. This enables the estimation of the tracking error. Furthermore the algorithm samples the parameters that govern the tracking process and therefore does not require any tweaking by the user. We demonstrate the algorithm on synthetic and single molecule data sets. Metrics for the comparison of SPT are generalised to be applied to a SPT sampler. We illustrate using the example of the diffusion coefficient how the distribution of the tracking solutions can be propagated into a distribution of derived quantities. We also discuss the major challenges that are posed by the realisation of a SPT sampler.
url https://doi.org/10.1371/journal.pone.0221865
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