https://github.com/gagneurlab/ocr-stats
https://github.com/gagneurlab/ocr-stats
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/gagneurlab/ocr-stats
- Owner: gagneurlab
- Created: 2017-11-29T18:44:22.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2023-01-10T00:19:08.000Z (over 2 years ago)
- Last Synced: 2025-03-25T14:38:59.747Z (about 2 months ago)
- Language: R
- Size: 255 KB
- Stars: 7
- Watchers: 5
- Forks: 2
- Open Issues: 1
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Metadata Files:
- Readme: readme.md
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README
# 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](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0199938).
## 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.