TRAIT2D: a software for quantitative analysis of single particle diffusion data
Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording...
| Main Authors: | , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
F1000Research
2021
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| _version_ | 1826309930491052032 |
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| author | Reina, F Wigg, JMA Dmitrieva, M Vogler, B Lefebvre, J Rittscher, J Eggeling, C |
| author_facet | Reina, F Wigg, JMA Dmitrieva, M Vogler, B Lefebvre, J Rittscher, J Eggeling, C |
| author_sort | Reina, F |
| collection | OXFORD |
| description | Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox – 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience. |
| first_indexed | 2024-03-07T07:43:05Z |
| format | Journal article |
| id | oxford-uuid:d6de7f0f-f45d-434d-afbe-8e7d57cb0f2d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:43:05Z |
| publishDate | 2021 |
| publisher | F1000Research |
| record_format | dspace |
| spelling | oxford-uuid:d6de7f0f-f45d-434d-afbe-8e7d57cb0f2d2023-05-05T15:41:26ZTRAIT2D: a software for quantitative analysis of single particle diffusion dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d6de7f0f-f45d-434d-afbe-8e7d57cb0f2dEnglishSymplectic ElementsF1000Research2021Reina, FWigg, JMADmitrieva, MVogler, BLefebvre, JRittscher, JEggeling, CSingle particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox – 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience. |
| spellingShingle | Reina, F Wigg, JMA Dmitrieva, M Vogler, B Lefebvre, J Rittscher, J Eggeling, C TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title | TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title_full | TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title_fullStr | TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title_full_unstemmed | TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title_short | TRAIT2D: a software for quantitative analysis of single particle diffusion data |
| title_sort | trait2d a software for quantitative analysis of single particle diffusion data |
| work_keys_str_mv | AT reinaf trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT wiggjma trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT dmitrievam trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT voglerb trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT lefebvrej trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT rittscherj trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata AT eggelingc trait2dasoftwareforquantitativeanalysisofsingleparticlediffusiondata |