# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
install.packages("jsonlite")
}
if (!requireNamespace("sigminer", quietly = TRUE)) {
remotes::install_github("ShixiangWang/sigminer")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
install.packages("ggplot2")
}
# Load packages
library(data.table)
library(jsonlite)
library(sigminer)
library(ggplot2)Group Rank Dotplot
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Group Rank Dotplot plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Values distribution for different groups.
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;sigminer;ggplot2
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
Biobase * 2.70.0 2025-10-29 [1] Bioconduc~
BiocGenerics * 0.56.0 2025-10-29 [1] Bioconduc~
data.table * 1.18.0 2025-12-24 [1] RSPM
generics * 0.1.4 2025-05-09 [1] RSPM
ggplot2 * 4.0.1 2025-11-14 [1] RSPM
jsonlite * 2.0.0 2025-03-27 [1] RSPM
sigminer * 2.3.1 2024-05-11 [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
* ββ Packages attached to the search path.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Data Preparation
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/grdotplot/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# View data
head(data) gvar dvar
1 A 0.4871212
2 A -0.1370275
3 A 0.1717455
4 A -0.9447939
5 A -1.2876203
6 A 1.4077657
Visualization
# Group Rank Dotplot
p <- show_group_distribution(data, gvar = "gvar", dvar = "dvar",
order_by_fun = F)
p
