Gene Ranking Dotplot

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

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: data.table; jsonlite; ggrepel; ggplot2; RColorBrewer

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
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(data.table)
library(jsonlite)
library(ggrepel)
library(ggplot2)
library(RColorBrewer)
sessioninfo::session_info("attached")
─ Session info ───────────────────────────────────────────────────────────────
 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

─ Packages ───────────────────────────────────────────────────────────────────
 package      * version date (UTC) lib source
 data.table   * 1.18.0  2025-12-24 [1] RSPM
 ggplot2      * 4.0.1   2025-11-14 [1] RSPM
 ggrepel      * 0.9.6   2024-09-07 [1] RSPM
 jsonlite     * 2.0.0   2025-03-27 [1] RSPM
 RColorBrewer * 1.1-3   2022-04-03 [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
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

Data Preparation

# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/gene-rank/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# 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
FigureΒ 1: Gene Ranking Dotplot