Bubble

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Bubble 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/bubble?lang=en

The bubble chart is a statistical chart that shows the third variable by the size of the bubble on the basis of the scatter chart, so that the three variables can be compared and analyzed simultaneously.

Setup

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

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}
if (!requireNamespace("stringr", quietly = TRUE)) {
  install.packages("stringr")
}

# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
library(stringr)

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
 ggplot2    * 4.0.1   2025-11-14 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM
 stringr    * 1.6.0   2025-11-04 [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 are GO Term,Gene Ridio, Gene count and P-value.

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

# convert data structure
data[, 1] <- str_to_sentence(str_remove(data[, 1], pattern = "\\w+:\\d+\\W"))
topnum <- 7
data <- data[1:topnum, ]
data[, 1] <- factor(data[, 1], level = rev(unique(data[, 1])))

# View data
head(data)

                               Term Count     Ratio   PValue
1                   Immune response    20 10.471204 9.61e-08
2     Defense response to bacterium    11  5.759162 3.02e-06
3                   Cell chemotaxis     8  4.188482 5.14e-06
4                     Cell adhesion    17  8.900524 2.73e-05
5             Complement activation     8  4.188482 3.56e-05
6 Extracellular matrix organization    11  5.759162 4.23e-05

Visualization

# Bubble
p <- ggplot(data, aes(Ratio, Term)) +
  geom_point(aes(size = Count, colour = -log10(PValue))) +
  scale_colour_gradient(low = "#00438E", high = "#E43535") +
  labs(colour = "-log10 (PValue)", size = "Count", x = "Ratio", y = "Term", 
       title = "Bubble Plot") +
  scale_x_continuous(limits = c(0, max(data$Ratio) * 1.2)) +
  guides(color = guide_colorbar(order = 1), size = guide_legend(order = 2)) +
  scale_y_discrete(labels = function(x) {str_wrap(x, width = 65)}) +
  theme_bw() +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_text(size = 12),
        axis.text = element_text(size = 10),
        axis.text.x = element_text(angle = 0, hjust = 0.5,vjust = 1),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p

The x-axis represents Gene Ridio, and the y-axis is GO Term; The size of the dot represents the number of genes, and the color of the dot represents the high or low P value.