# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
install.packages("jsonlite")
}
if (!requireNamespace("eulerr", quietly = TRUE)) {
install.packages("eulerr")
}
if (!requireNamespace("ggplotify", quietly = TRUE)) {
install.packages("ggplotify")
}
# Load packages
library(data.table)
library(jsonlite)
library(eulerr)
library(ggplotify)Eulerr Plot
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Eulerr Plot plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;eulerr;ggplotify
sessioninfo::session_info("attached")β Session info βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
setting value
version R version 4.5.2 (2025-10-31)
os Ubuntu 24.04.3 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate C.UTF-8
ctype C.UTF-8
tz UTC
date 2026-01-17
pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)
quarto 1.8.27 @ /usr/local/bin/quarto
β Packages βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
package * version date (UTC) lib source
data.table * 1.18.0 2025-12-24 [1] RSPM
eulerr * 7.0.4 2025-09-24 [1] RSPM
ggplotify * 0.1.3 2025-09-20 [1] RSPM
jsonlite * 2.0.0 2025-03-27 [1] RSPM
[1] /home/runner/work/_temp/Library
[2] /opt/R/4.5.2/lib/R/site-library
[3] /opt/R/4.5.2/lib/R/library
* ββ Packages attached to the search path.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Data Preparation
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/eulerr/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# convert data structure
genes <- as.numeric(data[, 2])
names(genes) <- as.character(data[, 1])
euler_set <- euler(genes)
# View data
head(data) Term Value
1 SE 13
2 Treat 28
3 Anti-CCP 101
4 DAS28 91
5 SE&Treat 1
6 SE&DAS28 14
Visualization
# Eulerr Plot
fill <- c("#3B4992FF","#EE0000FF","#008B45FF","#631879FF","#008280FF","#BB0021FF",
"#5F559BFF","#A20056FF")
p <- as.ggplot(
plot(euler_set,
labels = list(col = rep("white", length(genes))),
fills = list(fill = fill),
quantities = list(type = c("percent", "counts"),
col = rep("white", length(genes))),
main = "Eulerr")
)
p
