Barplot Gradient

Authors

[Editor] Hu Zheng;

[Contributors]

It is similar to the bubble chart, but on the basis of the histogram, a color gradient rectangle is used to simultaneously display the visualization of two variables.

Setup

  • System Requirements: Cross-platform (Linux/MacOS/Windows)

  • Programming language: R

  • Dependent packages: ggplot2; stringr

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

# Load packages
library(ggplot2)
library(stringr)

Data Preparation

The first column is Go Term (Go language code), the second column is the number of genes, and the third column is pvalue.

# Load data
data <- read.delim("files/Hiplot/008-barplot-gradient-data.txt", header = T)

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

Visualization

# Barplot Gradient
p <- ggplot(data, aes(x = Term, y = Count, fill = -log10(PValue))) +
  geom_bar(stat = "identity") +
  ggtitle("GO BarPlot") +
  scale_fill_continuous(low = "#00438E", high = "#E43535") +
  scale_x_discrete(labels = function(x) {str_wrap(x, width = 65)}) +
  labs(fill = "-log10 (PValue)", y = "Term", x = "Count") +
  coord_flip() +
  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),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p
FigureΒ 1: Barplot Gradient

As shown in the figure, blue is a low pvalue color, and red is a high pvalue color. As the pvalue increases, the color changes from blue to red. The abscissa indicates the number of genes.