# Install packages
if (!requireNamespace("ggplot2", quietly = TRUE)) {
install.packages("ggplot2")
}
# Load packages
library(ggplot2)
Custom Heatmap
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Custom Heatmap
plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Custom Heatmap, directly plot a heatmap based on the given data.
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
ggplot2
Data Preparation
The case data is a grayscale image of the official logo of hiplot.org.
# Load data
<- read.delim("files/Hiplot/034-custom-heat-map-data.txt", header = T)
data
# convert data structure
<- as.matrix(data[, 2:ncol(data)])
draw_data <- nrow(draw_data)
row_num <- ncol(draw_data)
col_num <- colnames(data)
col_labels <- col_labels[2:ncol(data)]
col_labels <- data$name
row_labels rm(data)
<- expand.grid(row = 1:row_num, col = 1:col_num)
df $value <- c(draw_data)
df
# View data
head(df)
row col value
1 1 1 236
2 2 1 236
3 3 1 236
4 4 1 236
5 5 1 236
6 6 1 236
Visualization
# Custom Heatmap
<- ggplot(df, aes(x = col, y = row, fill = value)) +
p geom_point(shape = 21, size = 8, aes(fill = value), color = "white") +
scale_fill_gradient(low = "#DDDDDD", high = "#0000F5") +
guides(fill = guide_colorbar(title = "Value")) +
theme(
panel.background = element_rect(fill = "white"),
panel.grid = element_blank(),
axis.text = element_text(size = 10),
axis.ticks = element_blank(),
axis.title = element_blank()
+
) scale_x_continuous(breaks = 1:col_num, labels = col_labels, position = "top") +
scale_y_reverse(breaks = 1:row_num, labels = row_labels, position = "left")
p
