Find foci

ImageJ and R scripts used in the analysis of foci formation during NF-kB nuclear translocation in B-cells.

Keywords: fluorescence microscopy, transcriptional regulation, transcription factor, NF-κB

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Prerequisites

• FIJI distribution of ImageJ2
• RStudio and R

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Files

ImageJ macro

ImageJ macro is available within the ijmacro directory. Detailed parameters of the ImageJ macro is explained in the pdf file located in the same directory.

Raw data

Example raw data and ImageJ macro outputs are supplied within the rawdata and imagej_output directories respectively.

Usage

Foci counting using ImageJ

1. Download the following ImageJ macro: link
2. Open raw files using FIJI.
3. Open focicount.ijm within the ijmacro.zip using FIJI.
4. Edit the following parameters on the macro window for foci counting.
   • diameterROI: Diameter of the foci in pixel (default = 6)
   • FMaxNoise : Noise threshold under find maxima (default = 6000)
   • diameterCell : Diameter of the cells in pixel (default = 60)
   • DotsMax : Threshold for final foci counting from sharpened image (default = 10000)
5. Run macro (ctrl + R).
6. Specify output directory (preferably inside imagej_output directory).
7. Remove unwanted cells using mouse click.
8. Click OK and Continue to export the result files to the specified directory.

Foci count analysis and visualization using RStudio

1. Install package

Requirements:

• shiny

• ggplot2

• dplyr

  devtools::install_github("johannesnicolaus/findfoci")

2. Run the following commands to summarize the number of foci within each cell and save the resulting data frame as results.csv to the current directory. Specify dose unit and time unit according to the file name.

   findfoci::count_foci("DIRECTORY_OF_IMAGEJ_OUTPUT", dose = "ugml", time = "min")
   write.csv("results.csv")

3. Run the Shiny app for data visualization.

   findfoci::heatscatter()

4. Using Shiny app interface, click the button browse and browse for the results.csv file.

5. Change different visualization parameters using the user interface of the Shiny app.

   • Data summarisation: choose how to summarize data for the line plot. (Default: median)
   • Jitter width : specifies the width of the jitter plot.
   • Data transformation method: choose how to transform the data for easier visualization. (Default: log2(n+1))
   • Plot title
   • Plot, X axis, and Y axis title
   • Y axis range

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Authors

• Johannes Nicolaus Wibisana - ImageJ Macro improvements, R package
• Takehiko Inaba - ImageJ Macro

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

• Yasushi Sako (Cellular Informatics Laboratory, RIKEN) for discussions and improvements to the analysis.