MitoGraph-Contrib-RScripts

Here we provide an example dataset of mammalian cells and R scripts created to assist you in analyzing and plotting the data produced by MitoGraph. Example of a plot generated by the CreatePlots.R script:

Download

Click here to download our example dataset and R scripts. We recommend unzipping the file in your Desktop.

How to Run MitoGraph on our example dataset

First download the program and follow the instructions for use of MitoGraph

To execute MitoGraph on our test dataset, type the following command in the terminal of your Mac OS (spotlight + terminal):

cd ~/Desktop/MitoGraph
./MitoGraph -xy 0.1667 -z 0.2 -scales 1.0 1.3 4 -adaptive 10 -path ~/Desktop/MitoGraph-Contrib-RScripts-1.0/samples

How to use our scripts

1. Before running our scripts, make sure to install:

• R as well as R Studio (https://www.rstudio.com/products/rstudio/download/)
• R packages: igraph, ggplot2, reshape2, formattable and RColorBrewer.

2. Copy/save CreateSummary.R and CreatePlots.R to the folder containing the MitoGraph output files.

3. Open CreateSummary.R with R Studio. Set working directory to source file location (session -> set working directory -> to source file location)

4. Copy the working directory path to the portion of the script that specifies the location of the Gnets files

GnetsFolder <- "~/Desktop/MitoGraph-Contrib-RScripts-1.0/samples/"

5. Run CreateSummary.R with "Command + Option + r"

6. Add a column (in the second column position) called Condition in the file output-summary.csv created in the previous step and fill in with the corresponding cell condition.

7. Open CreatePlots.R with R Studio. Set working directory to source file location (session -> set working directory -> to source file location)

8. Copy the working directory path to the portion of the script that specifies the location of the Gnets files

GnetsFolder <- "~/Desktop/MitoGraph-Contrib-RScripts-1.0/samples/"

9. Run CreatePlots.R with "Command + Option + r"

Output files

CreateSummary.R output files:

• output.csv
• output-summary.csv

CreatePlots.R output files:

• Plot1.eps: Avg edge length vs. Total Connected Components (normalized to total length (µm))

• Plot3.eps: Total edge # (normalized to total length (µm)) vs. Average Degree

• Plot5.eps: Total connected components (normalized to total length (µm) vs. PHI

• Plot7.eps: Avg mitochondrial width (µm) vs Volume from voxels (µm^3)

• AVG_SD_metrics.eps: Bar chart of all metrics collected (Avg±STDEV)

• All_metrics.eps: Box plot + Scatter overlay plot of all metrics collected

• MitoGraph_Connectivity_score.eps: Box plot + Scatter overlay plot of the MitoGraph Connectivity Score

• AOV_stats_new.csv: Table of p-values

References:

MitoGraph: Matheus P Viana, Swee Lim, Susanne M Rafelski, Quantifying Mitochondrial Content in Living Cells (2015), Biophysical Methods in Cell Biology, (125) - 77-93 (http://www.sciencedirect.com/science/article/pii/S0091679X14000041)

MitoGraph on mammalian cells: Megan C. Harwig, Matheus P. Viana, John M. Egner, Jason J. Harwig, Michael E. Widlansky, Susanne M. Rafelski, R. Blake Hill, Methods for imaging mammalian mitochondrial morphology: a prospective on MitoGraph (2018), Analytical Biochemistry, (552) - 81-99 https://doi.org/10.1016/j.ab.2018.02.022

R: R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

igraph: Csardi G, Nepusz T: The igraph software package for complex network research, InterJournal, Complex Systems 1695. 2006. http://igraph.org

ggplot2: H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

reshape2: Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20. URL http://www.jstatsoft.org/v21/i12/.

formattable: Kun Ren and Kenton Russell (2016). formattable: Create 'Formattable' Data Structures. R package version 0.2.0.1. https://CRAN.R-project.org/package=formattable

RColorBrewer: Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes. R package version 1.1-2. https://CRAN.R-project.org/package=RColorBrewer