https://github.com/quantixed/superplotr
Making SuperPlots in R
https://github.com/quantixed/superplotr
dataviz ggplot superplot
Last synced: 10 months ago
JSON representation
Making SuperPlots in R
- Host: GitHub
- URL: https://github.com/quantixed/superplotr
- Owner: quantixed
- License: other
- Created: 2024-12-08T21:49:03.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-03-07T13:30:52.000Z (11 months ago)
- Last Synced: 2025-03-07T14:26:59.472Z (11 months ago)
- Topics: dataviz, ggplot, superplot
- Language: R
- Homepage: https://quantixed.github.io/SuperPlotR/
- Size: 8.05 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# SuperPlotR 
[](https://doi.org/10.5281/zenodo.14606751)
The goal of SuperPlotR is to allow the user to easily generate SuperPlots in R.
SuperPlots are a way to visualise data in a way that emphasises the experimental
reproducibility.
You can read more about SuperPlots in the
[original paper](https://doi.org/10.1083/jcb.202001064):
Lord, S.J., Velle, K.B., Mullins, R.D. & Fritz-Laylin, L.K. (2020)
**SuperPlots: Communicating reproducibility and variability in cell biology.**
_J. Cell Biol._ 219(6):e202001064
## Installation
You can install the development version of SuperPlotR from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("quantixed/SuperPlotR")
```
## Example
A simple example of how to use SuperPlotR is shown below:
```{r example}
library(SuperPlotR)
superplot(lord_jcb, "Speed", "Treatment", "Replicate", ylab = "Speed (µm/min)")
```
The data used in this example is included in the package and is from the original
paper.
To generate a SuperPlot, you need a data frame that has at least three columns.
These columns are:
1. the variable that is measured in the experiment,
2. the experimental condition,
3. the experimental repeat that the measurment comes from.
The `superplot` function takes the data frame, the names of these three columns,
and is further customisable with additional arguments.
See `vignette("SuperPlotR")` for more examples, or
`vignette("advanced")` for more advanced usage.
## More information
My SuperPlot package for IGOR Pro is available
[here](https://github.com/quantixed/SuperPlot)
A popular web-based app for generating SuperPlots, developed by
[Joachim Goedhart](https://github.com/JoachimGoedhart) is available
[here](https://huygens.science.uva.nl/SuperPlotsOfData/)