Radar

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Radar plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:

https://hiplot.cn/basic/radar?lang=en

Radar chart displays multivariable data in the form of two-dimensional charts representing three or more quantitative variables on the axis starting from the same point, so as to visually express the comparison of a research object in multiple parameters.

Setup

System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages: data.table; jsonlite; ggradar; dplyr; scales; tibble; ggplot2

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("ggradar", quietly = TRUE)) {
  remotes::install_github("ricardo-bion/ggradar", dependencies = TRUE)
}
if (!requireNamespace("dplyr", quietly = TRUE)) {
  install.packages("dplyr")
}
if (!requireNamespace("scales", quietly = TRUE)) {
  install.packages("scales")
}
if (!requireNamespace("tibble", quietly = TRUE)) {
  install.packages("tibble")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}

# Load packages
library(data.table)
library(jsonlite)
library(ggradar)
library(dplyr)
library(scales)
library(tibble)
library(ggplot2)

sessioninfo::session_info("attached")

─ Session info ───────────────────────────────────────────────────────────────
 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

─ Packages ───────────────────────────────────────────────────────────────────
 package    * version date (UTC) lib source
 data.table * 1.18.0  2025-12-24 [1] RSPM
 dplyr      * 1.1.4   2023-11-17 [1] RSPM
 ggplot2    * 4.0.1   2025-11-14 [1] RSPM
 ggradar    * 0.2     2025-11-02 [1] Github (ricardo-bion/ggradar@f99517a)
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM
 scales     * 1.4.0   2025-04-24 [1] RSPM
 tibble     * 3.3.1   2026-01-11 [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
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

Data Preparation

The loaded data is data set (expression levels of 5 genes in 4 diseases).

# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/radar/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# Convert data structure
data <- as.data.frame(t(data))
colnames(data) <- data[1, ]
data <- data[-1, ]
for (i in seq_len(ncol(data))) {
  data[, i] <- as.numeric(data[, i])
}
data_radar <- data %>%
  rownames_to_column(var = "sample")
data_radar <- data_radar %>% mutate_at(vars(-sample), rescale)

# View data
head(data)

   value1 value2 value3 value4 value5
S1      6    160    110   3.90  2.620
S2      6    160    110   3.90  2.875
S3      4    108     93   3.85  2.320
S4      6    258    110   3.08  3.215

Visualization

# Radar
p <- ggradar(data_radar, gridline.max.linetype = 1, group.point.size = 4,
             group.line.width = 1, font.radar = "Arial", fill.alpha = 0.5,
             gridline.min.colour = "grey", gridline.mid.colour = "#007A87",
             gridline.max.colour = "grey") +
  ggtitle("Radar Plot") +
  scale_color_manual(values = c("#E64B35FF","#4DBBD5FF","#00A087FF","#3C5488FF")) +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_blank(),
        axis.text = element_text(size = 10),
        axis.text.x = element_blank(),
        axis.title.y=element_blank(),
        axis.ticks.y=element_blank(),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))
 
p

Each color of the radar map represents a disease, and the position of each point represents different gene expression. The higher the gene expression value, the farther away it is from the center of the circle, and vice versa.