TockyPrep

Data Preprocessing for Fluorescent Timer Reporters Using the Timer-Of-Cell-Kinetics-of-activitY (Tocky)

TockyPrep: Data Preprocessing Methods for Fluorescent Timer Reporter Data

Author: Dr. Masahiro Ono
Date: 24 November 2024

Link to the TockyPrep Documentation Page

Introduction - The R Package for Fluorescent Timer Data Analysis

The potential of Fluorescent Timer proteins

Fluorescent Timer proteins uniquely alter their emission spectra over time, making them powerful tools for monitoring dynamic cellular processes. These proteins are pivotal for understanding the intricate temporal dynamics of cellular events. Despite their potential, analyzing Timer fluorescence data in flow cytometry is often hampered by variability in instrument settings and the lack of standardized data preprocessing methods.

A Breakthrough in Fluorescent Timer Analysis

A significant advancement was made in 2018 when the Ono lab introduced Tocky, a novel concept for analyzing Fluorescent Timer data. This approach encompasses data normalization and transformation methods (see Introduction of the TockyPrep Package). However, a computational implementation of this methodology was not yet available.

Aim of the TockyPrep Package

To address these challenges, the TockyPrep package has been developed. This R package provides a comprehensive suite of tools designed to automate the preprocessing, normalization, and trigonometric transformation of Timer fluorescence data, facilitating more accurate and reproducible analyses.

The TockyPrep package aims to standardize the analysis of Timer fluorescence to improve reproducibility and accuracy across various experimental setups. It specifically addresses the normalization of immature and mature Timer fluorescence as a critical step for robust analysis. This approach is central to understanding the maturation dynamics of Timer proteins, and is implemented using advanced trigonometric transformations.

The TockyPrep R Package

The TockyPrep R package provides data preprocessing methods for Fluorescent Timer data for analyzing temporal dynamics in cellular activities using flow cytometry.

Key Features of TockyPrep

Specifically, the TockyPrep package provides essential data preprocessing methods for analyzing Fluorescent Timer data:

  1. Timer Fluorescence Normalization:

    • This feature corrects for any instrumental biases that may affect the fluorescence readings, ensuring that the measurements of Timer Blue and Timer Red fluorescence are accurate and comparable across different experimental setups. This normalization is crucial for accurate assessment of the maturation state of the Timer protein, as it adjusts for variability in the signal intensity between different cells and samples.

  2. Timer Fluorescence Thresholding:

    • To enhance the reliability of Timer data analysis, this method filters out background noise by setting thresholds that distinguish between Timer-positive and Timer-negative cells. This is vital for focusing the analysis on cells that express the Timer protein, thereby eliminating data points that could distort the interpretation of temporal dynamics.

  3. Trigonometric Transformation:

    • This transformation computes two new metrics, Timer Angle and Timer Intensity, from the normalized fluorescence data. These metrics are pivotal for quantifying the dynamics of Timer protein maturation within cells, providing insights into the timing and progression of cellular events.

  4. Sample Definition:

    • TockyPrep aids in organizing and labeling flow cytometry data files for streamlined analysis. It automates the identification of sample groups and control samples, facilitating more efficient subsequent data analyses.

  5. Visualization Tools:

    • The package includes functions to visualize both raw and transformed Timer fluorescence data. These tools allow users to generate plots that illustrate the distribution of Timer fluorescence within samples or to track the transformation results, such as plotting Timer Angle versus Timer Intensity. These visualizations are crucial for preliminary data assessment, enabling researchers to quickly identify trends or anomalies that warrant further investigation.

Availability

  • TockyPrep is freely available for distribution via GitHub:

Link to the repository: TockyPrep on GitHub

The scehametic figure below provides an overview on the workflows within TockyPrep.

Getting Started with TockyPrep

To begin using TockyPrep, install the package from GitHub using the following command:

# Install TockyPrep from GitHub
devtools::install_github("MonoTockyLab/TockyPrep")

4. Package Documentation

The TockyPrep package documentation is available online:

This site includes all the function reference manuals and vignettes (tutorials).

In addition to the HTML manual pages, a PDF manual for the TockyPrep package is available. You can find it in the installed package directory under doc/, or you can access it directly from GitHub.


All code and original graphical content within the TockyPrep package, including anime-like characters and logos, are copyrighted by Masahiro Ono.

License

The distribution and modification are governed by the Apache License 2.0, which ensures that all users have the freedom to use and change the software in a way that respects the original authorship. See the LICENSE file for more information.

Citing TockyPrep

If you use TockyPrep in your research, please cite (missing reference):

Masahiro Ono (2024). TockyPrep: Data Preprocessing Methods for Flow Cytometric Fluorescent Timer Analysis. arXiv:2411.04111 [q-bio.QM]. Available at:https://arxiv.org/abs/2411.04111.

Masahiro Ono (2025). TockyPrep: Data Preprocessing Methods for Flow Cytometric Fluorescent Timer Analysis. BMC Bioinformatics, 26, 44. Available at:https://doi.org/10.1186/s12859-025-06058-8.

BibTeX Entry

@article{ono2024TockyPrep,
    title={TockyPrep: Data Preprocessing Methods for Flow Cytometric Fluorescent Timer Analysis},
    author={Masahiro Ono},
    year={2024},
    journal={arXiv:2411.04111 [q-bio.QM]},
    url={https://arxiv.org/abs/2411.04111},
}

@article{tockyprep2025,
    title={TockyPrep: Data Preprocessing Methods for Flow Cytometric Fluorescent Timer Analysis},
    author={Masahiro Ono},
    year={2024},
    journal={BMC Bioinformatics},
    year = "2025",
    volume = "26",
    pages = "44",
    url={https://doi.org/10.1186/s12859-025-06058-8},
}

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