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OCR-Stats

Contains functions to estimate oxygen consumption rates using the Seahorse XF Analyzer, and perform statistical testing between samples. Includes plotting functions as well. Manuscript in Plos ONE.

Installing requirements

R

Install the following R packages using install.packages():

  • data.table
  • dplyr
  • ggplot2
  • ggthemes
  • magrittr
  • plotly
  • tidyr

General repository organization notes

Source the config.R file to load all necessary functions and variables. Go through the example.R which should give a direct idea of the functions and plots available.

There are 2 folders:

  • functions: contains different functions needed for the statistical OCR-stats methods.
  • plots: contains different plot functions. They are all created using ggplot, therefore they can be saved and edited.

R should be started from the repository root.

All data located in data/.

Main functions explained

  • add_outlier_col(): adds 2 T/F columns (is.outw and is.out) to the given dataset indicating if the OCR value is a well level or single point outlier.
  • compute_bionergetics(): computes all four OCR interval levels in natural and log scales. Also provides bioenergetics in the natural scale (eg. maximal respiration) and in the log scale (eg. M/Ei ratio)
  • stat_test_OCR(): compares the bioenergetics of 2 samples providing an estimate with the difference and pvalue. Returns a list with 2 objects: dif_dt: for each pair of samples to be compared, gives the bioenergetics of each of them, and the respective difference; pv_dt: for each sample, returns one between-plates replicates aggregated difference wrt to a control and a pvalue.
  • sh_plot(): plots a whole Seahorse experiment, differentiating samples by color. Can produce points, boxplots or violin plots. Returns a ggplot object that can be further edited.
  • outlier_plot(): plots a single sample, highlighting outlier status. Returns a ggplot object that can be further edited.
  • plot_bios(): plots the specified bioenergetics difference wrt to a control of all samples. Marks as red significant samples.
  • sh_volcano(): creates a volcano plot, where the x axis is the bioenergetic difference wrt a control and the y-axis the -log10 of the pvalue. Samples above the horizontal dotted line are significant.
  • scatterplot_bios(): creates a scatterplot of 2 different bioenergetic differences.

Support

Let me know if you have any problems by creating an issue or sending an email to yepez-at-in.tum.de.