Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data
In this study, we introduce Blob-B-Gone, a lightweight framework to computationally differentiate and eventually remove dense isotropic localization accumulations (blobs) caused by artifactually immobilized particles in MINFLUX single-particle tracking (SPT) measurements. This approach uses purely g...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Bioinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2023.1268899/full |
| _version_ | 1797461164198723584 |
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| author | Bela T. L. Vogler Bela T. L. Vogler Francesco Reina Christian Eggeling Christian Eggeling Christian Eggeling Christian Eggeling |
| author_facet | Bela T. L. Vogler Bela T. L. Vogler Francesco Reina Christian Eggeling Christian Eggeling Christian Eggeling Christian Eggeling |
| author_sort | Bela T. L. Vogler |
| collection | DOAJ |
| description | In this study, we introduce Blob-B-Gone, a lightweight framework to computationally differentiate and eventually remove dense isotropic localization accumulations (blobs) caused by artifactually immobilized particles in MINFLUX single-particle tracking (SPT) measurements. This approach uses purely geometrical features extracted from MINFLUX-detected single-particle trajectories, which are treated as point clouds of localizations. Employing k-means++ clustering, we perform single-shot separation of the feature space to rapidly extract blobs from the dataset without the need for training. We automatically annotate the resulting sub-sets and, finally, evaluate our results by means of principal component analysis (PCA), highlighting a clear separation in the feature space. We demonstrate our approach using two- and three-dimensional simulations of freely diffusing particles and blob artifacts based on parameters extracted from hand-labeled MINFLUX tracking data of fixed 23-nm bead samples and two-dimensional diffusing quantum dots on model lipid membranes. Applying Blob-B-Gone, we achieve a clear distinction between blob-like and other trajectories, represented in F1 scores of 0.998 (2D) and 1.0 (3D) as well as 0.995 (balanced) and 0.994 (imbalanced). This framework can be straightforwardly applied to similar situations, where discerning between blob and elongated time traces is desirable. Given a number of localizations sufficient to express geometric features, the method can operate on any generic point clouds presented to it, regardless of its origin. |
| first_indexed | 2024-03-09T17:15:31Z |
| format | Article |
| id | doaj.art-a9b5a7d623334736a64c429dfd0d3784 |
| institution | Directory Open Access Journal |
| issn | 2673-7647 |
| language | English |
| last_indexed | 2024-03-09T17:15:31Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj.art-a9b5a7d623334736a64c429dfd0d37842023-11-24T13:39:58ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472023-11-01310.3389/fbinf.2023.12688991268899Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking dataBela T. L. Vogler0Bela T. L. Vogler1Francesco Reina2Christian Eggeling3Christian Eggeling4Christian Eggeling5Christian Eggeling6Leibniz Institute of Photonic Technology e.V., Member of the Leibniz Centre for Photonics in Infection Research (LPI), Jena, GermanyInstitute of Applied Optics and Biophysics, Faculty of Physics and Astronomy, Friedrich Schiller University Jena, Jena, GermanyLeibniz Institute of Photonic Technology e.V., Member of the Leibniz Centre for Photonics in Infection Research (LPI), Jena, GermanyLeibniz Institute of Photonic Technology e.V., Member of the Leibniz Centre for Photonics in Infection Research (LPI), Jena, GermanyInstitute of Applied Optics and Biophysics, Faculty of Physics and Astronomy, Friedrich Schiller University Jena, Jena, GermanyJena Center for Soft Matter, Friedrich Schiller University Jena, Jena, GermanyAbbe Center of Photonics, Friedrich Schiller University Jena, Jena, GermanyIn this study, we introduce Blob-B-Gone, a lightweight framework to computationally differentiate and eventually remove dense isotropic localization accumulations (blobs) caused by artifactually immobilized particles in MINFLUX single-particle tracking (SPT) measurements. This approach uses purely geometrical features extracted from MINFLUX-detected single-particle trajectories, which are treated as point clouds of localizations. Employing k-means++ clustering, we perform single-shot separation of the feature space to rapidly extract blobs from the dataset without the need for training. We automatically annotate the resulting sub-sets and, finally, evaluate our results by means of principal component analysis (PCA), highlighting a clear separation in the feature space. We demonstrate our approach using two- and three-dimensional simulations of freely diffusing particles and blob artifacts based on parameters extracted from hand-labeled MINFLUX tracking data of fixed 23-nm bead samples and two-dimensional diffusing quantum dots on model lipid membranes. Applying Blob-B-Gone, we achieve a clear distinction between blob-like and other trajectories, represented in F1 scores of 0.998 (2D) and 1.0 (3D) as well as 0.995 (balanced) and 0.994 (imbalanced). This framework can be straightforwardly applied to similar situations, where discerning between blob and elongated time traces is desirable. Given a number of localizations sufficient to express geometric features, the method can operate on any generic point clouds presented to it, regardless of its origin.https://www.frontiersin.org/articles/10.3389/fbinf.2023.1268899/fullartifact removalMINFLUXsingle-particle trackingclusteringannotationpoint clouds |
| spellingShingle | Bela T. L. Vogler Bela T. L. Vogler Francesco Reina Christian Eggeling Christian Eggeling Christian Eggeling Christian Eggeling Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data Frontiers in Bioinformatics artifact removal MINFLUX single-particle tracking clustering annotation point clouds |
| title | Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data |
| title_full | Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data |
| title_fullStr | Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data |
| title_full_unstemmed | Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data |
| title_short | Blob-B-Gone: a lightweight framework for removing blob artifacts from 2D/3D MINFLUX single-particle tracking data |
| title_sort | blob b gone a lightweight framework for removing blob artifacts from 2d 3d minflux single particle tracking data |
| topic | artifact removal MINFLUX single-particle tracking clustering annotation point clouds |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2023.1268899/full |
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