TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis
Abstract Background: Fluorescent Timer proteins, which display time-dependent changes in their emission spectra, are invaluable for analyzing the temporal dynamics of cellular events at the single-cell level. We previously developed the Timer-of-cell-kinetics-and-activity (Tocky) tools, utilizing a...
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BMC
2025-02-01
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| Series: | BMC Bioinformatics |
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| Online Access: | https://doi.org/10.1186/s12859-025-06058-8 |
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| author | Masahiro Ono |
| author_facet | Masahiro Ono |
| author_sort | Masahiro Ono |
| collection | DOAJ |
| description | Abstract Background: Fluorescent Timer proteins, which display time-dependent changes in their emission spectra, are invaluable for analyzing the temporal dynamics of cellular events at the single-cell level. We previously developed the Timer-of-cell-kinetics-and-activity (Tocky) tools, utilizing a specific Timer protein, Fast-FT, to monitor temporal changes in cellular activities. Despite their potential, the analysis of Timer fluorescence in flow cytometry is frequently compromised by variability in instrument settings and the absence of standardized preprocessing methods. The development and implementation of effective data preprocessing methods remain to be achieved. Results: In this study, we introduce the R package that automates the data preprocessing of Timer fluorescence data from flow cytometry experiments for quantitative analysis at single-cell level. Our aim is to standardize Timer data analysis to enhance reproducibility and accuracy across different experimental setups. The package includes a trigonometric transformation method to elucidate the dynamics of Fluorescent Timer proteins. We have identified the normalization of immature and mature Timer fluorescence data as essential for robust analysis, clarifying how this normalization affects the analysis of Timer maturation. These preprocessing methods are all encapsulated within the TockyPrep package. Conclusions: TockyPrep is available for distribution via GitHub at https://github.com/MonoTockyLab/TockyPrep , providing tools for data preprocessing and basic visualization of Timer fluorescence data. This toolkit is expected to enhance the utility of experimental systems utilizing Fluorescent Timer proteins, including the Tocky tools. |
| format | Article |
| id | doaj-art-a814937d03754642b8e4b233bc90b65e |
| institution | Kabale University |
| issn | 1471-2105 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj-art-a814937d03754642b8e4b233bc90b65e2025-02-09T12:57:00ZengBMCBMC Bioinformatics1471-21052025-02-0126111610.1186/s12859-025-06058-8TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysisMasahiro Ono0Department of Life Sciences, Imperial College LondonAbstract Background: Fluorescent Timer proteins, which display time-dependent changes in their emission spectra, are invaluable for analyzing the temporal dynamics of cellular events at the single-cell level. We previously developed the Timer-of-cell-kinetics-and-activity (Tocky) tools, utilizing a specific Timer protein, Fast-FT, to monitor temporal changes in cellular activities. Despite their potential, the analysis of Timer fluorescence in flow cytometry is frequently compromised by variability in instrument settings and the absence of standardized preprocessing methods. The development and implementation of effective data preprocessing methods remain to be achieved. Results: In this study, we introduce the R package that automates the data preprocessing of Timer fluorescence data from flow cytometry experiments for quantitative analysis at single-cell level. Our aim is to standardize Timer data analysis to enhance reproducibility and accuracy across different experimental setups. The package includes a trigonometric transformation method to elucidate the dynamics of Fluorescent Timer proteins. We have identified the normalization of immature and mature Timer fluorescence data as essential for robust analysis, clarifying how this normalization affects the analysis of Timer maturation. These preprocessing methods are all encapsulated within the TockyPrep package. Conclusions: TockyPrep is available for distribution via GitHub at https://github.com/MonoTockyLab/TockyPrep , providing tools for data preprocessing and basic visualization of Timer fluorescence data. This toolkit is expected to enhance the utility of experimental systems utilizing Fluorescent Timer proteins, including the Tocky tools.https://doi.org/10.1186/s12859-025-06058-8Fluorescent Timer ProteinTockyFlow CytometryData preprocessingNr4a3-Tocky |
| spellingShingle | Masahiro Ono TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis BMC Bioinformatics Fluorescent Timer Protein Tocky Flow Cytometry Data preprocessing Nr4a3-Tocky |
| title | TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis |
| title_full | TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis |
| title_fullStr | TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis |
| title_full_unstemmed | TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis |
| title_short | TockyPrep: data preprocessing methods for flow cytometric fluorescent timer analysis |
| title_sort | tockyprep data preprocessing methods for flow cytometric fluorescent timer analysis |
| topic | Fluorescent Timer Protein Tocky Flow Cytometry Data preprocessing Nr4a3-Tocky |
| url | https://doi.org/10.1186/s12859-025-06058-8 |
| work_keys_str_mv | AT masahiroono tockyprepdatapreprocessingmethodsforflowcytometricfluorescenttimeranalysis |