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https://github.com/matbou85/ggScatRidges
This is a useful function to help the user to better visualise the distribution between sample groups using density plots combined to a scatter plot.
https://github.com/matbou85/ggScatRidges
ggplot2 ggridges plotting r
Last synced: about 2 months ago
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This is a useful function to help the user to better visualise the distribution between sample groups using density plots combined to a scatter plot.
- Host: GitHub
- URL: https://github.com/matbou85/ggScatRidges
- Owner: matbou85
- License: gpl-3.0
- Created: 2023-11-09T08:59:20.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-02-21T07:34:52.000Z (7 months ago)
- Last Synced: 2024-07-26T15:44:32.684Z (2 months ago)
- Topics: ggplot2, ggridges, plotting, r
- Language: R
- Homepage:
- Size: 1.39 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ggScatRidges: Scatter Plot Combined with Ridgelines in 'ggplot2'
`ggScatRidges` is a simple function combining a scatter plot to a ridgeline plot to visualise the disparities of the data points. This helps visualising the distribution of different groups in the data.
## Installation
Please install the stable release from CRAN:
``` r
install.packages("ggScatRidges")
```
Alternatively, you can install the latest development version from github:
``` r
remotes::install_github("matbou85/ggScatRidges")
```
## Basic usage
``` r
library(ggScatRidges)
ggScatRidges(x = iris$Sepal.Length, y = iris$Sepal.Width, group= iris$Species,
color = "lancet", ridges = TRUE, title = "plot iris", legend.title = "Grouping",
xlab = "Sepal.Length", ylab = "Sepal.Width", base_size = 15, size = 2,
draw = TRUE, density_2d = TRUE, legend = TRUE, label = FALSE, text = NULL)
```
## Change parameters: remove legend, change points shape and size
```r
library(ggScatRidges)
ggScatRidges(x = iris$Sepal.Length, y = iris$Sepal.Width, group= iris$Species,
color = "lancet", ridges = TRUE, title = "plot iris",
xlab = "Sepal.Length", ylab = "Sepal.Width", base_size = 15, size = 3, draw = TRUE,
density_2d = FALSE, legend = FALSE, label = FALSE, text = NULL, pch = c(10,12,14))
```
## PCA usage application
``` r
library(ggScatRidges)
library(factoextra)
pca <- prcomp(iris[,1:4])
PC1=pca$x[,1]
PC2=pca$x[,2]
eig.val <- get_eigenvalue(pca)
xlab <- paste0("PC1: ", round(eig.val[1,3], digits = 1), "% variance")
ylab <- paste0("PC2: ", round(eig.val[2,3] - eig.val[1,3], digits = 1), "% variance")
ggScatRidges(x = PC1, y = PC2, group= iris$Species,
color = "lancet", ridges = TRUE, title = "PCA iris",
xlab = xlab, ylab = ylab, size = 2, draw = TRUE,
density_2d = TRUE, legend = TRUE, label = FALSE, text = NULL)
```
## Plot from dataframe
``` r
library(ggScatRidges)
library(dplyr)
iris2 <- iris[,c(1,2,5)] ## The first column will be used as 'x', the second as 'y' and the third as group for plotting.
iris2 <- iris2 %>% group_by(Species) %>% slice(1:10)
iris2$name <- c(1:30) ## The fourth column is used for naming.
ggScatRidges(x = iris2,
color = "lancet", ridges = TRUE, title = "plot iris",
xlab = "Sepal.Length", ylab = "Sepal.width", size = 2, draw = TRUE,
density_2d = FALSE, legend = TRUE, label = TRUE)
```
This function is loosely inspired by one of the plots in [a post](http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/78-perfect-scatter-plots-with-correlation-and-marginal-histograms/) by [Alboukadel Kassambara](http://www.sthda.com/english/user/profile/1) from 2017.