Gene Ranking Dotplot

Authors

[Editor] Hu Zheng;

[Contributors]

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Gene Ranking Dotplot 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/gene-rank?lang=en

Gene expression ranking visualization.

Setup

System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages: ggrepel; ggplot2; RColorBrewer

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

# Load packages
library(ggrepel)
library(ggplot2)
library(RColorBrewer)

Data Preparation

# Load data
data <- read.delim("files/Hiplot/061-gene-rank-data.txt", header = T)

# Convert data structure
## ordered by log2FoldChange and pvalue
data <- data[order(-data$log2FC, data$pvalue), ]
## add the rank column
data$rank <- 1:nrow(data)
## get the top n up and down gene for labeling
top_n <- 5
top_n_up <- rownames(head(data, top_n))
top_n_down <- rownames(tail(data, top_n))
genes_to_label <- c(top_n_up, top_n_down)
data2 <- data[genes_to_label, ]


# View data
head(data)

        gene   log2FC       pvalue rank
514 LOC91370 3.889820 8.478310e-03    1
293   LRRC25 3.492413 5.000000e-05    2
470   BEGAIN 3.312996 3.347634e-03    3
159   RDM1P5 3.125070 1.538852e-02    4
194    CLDN1 3.096516 2.622163e-02    5
626    KCNS1 2.949729 2.770000e-09    6

Visualization

# Gene Ranking Dotplot
p <- 
  ggplot(data, aes(rank, log2FC, color = pvalue, size = abs(log2FC))) + 
  geom_point() + 
  scale_color_gradientn(colours = colorRampPalette(brewer.pal(11,'RdYlBu'))(100)) +
  geom_hline(yintercept = c(-1, 1), linetype = 2, size = 0.3) +
  geom_hline(yintercept = 0, linetype = 1, size = 0.5) +
  geom_vline(xintercept = median(data$rank), linetype = 2, size = 0.3) + 
  geom_text_repel(data = data2, aes(rank, log2FC, label = gene),
                  size = 3, color = "red") +
  xlab("") + ylab("") + 
  ylim(c(-max(abs(data$log2FC)), max(abs(data$log2FC)))) +
  labs(color = "Pvalue", size = "Log2FoldChange") +
  theme_bw(base_size = 12) +
  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