# 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("sigminer", quietly = TRUE)) {
BiocManager::install("sigminer")
}
# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
library(sigminer)Simplified Correlation Heatmap
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Simplified Correlation Heatmap plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Simplified variables correlation heatmap
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;ggplot2;ggisoband
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 2026-01-27
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/cor-heatmap-simple/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# View data
head(data) mpg cyl disp hp drat wt qsec vs am gear carb
1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
5 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
6 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
Visualization
# Simplified Correlation Heatmap
p <- show_cor(
data = data,
x_vars = c("mpg","cyl","disp"),
y_vars = c("wt","hp","drat"),
cor_method = "pearson",
vis_method = "square",
lab = T,
test = T,
hc_order = F,
legend.title = "Corr"
) +
ggtitle("") +
labs(x="", y="") +
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 = 45, hjust = 1, vjust = 1),
legend.position = "right",
legend.direction = "vertical",
legend.title = element_text(size = 10),
legend.text = element_text(size = 10))
p
