旭日图简介
旭日图（Sunburst Chart），其实是一种特殊的饼图或环状图，常用于展示数据的多层数据结构关系。
标签：#微生物组数据分析 #MicrobiomeStatPlot #旭日图 #R语言可视化 #sunburst plot
作者：First draft(初稿)：Defeng Bai(白德凤)；Proofreading(校对)：Ma Chuang(马闯) and Jiani Xun(荀佳妮)；Text tutorial(文字教程)：Defeng Bai(白德凤)
源代码及测试数据链接：
https://github.com/YongxinLiu/MicrobiomeStatPlot/项目中目录 3.Visualization_and_interpretation/SunBurst_Chart
或公众号后台回复“MicrobiomeStatPlot”领取
下图是Ana Rita Brochado团队2024年发表在Nature Microbiology（Brenzinger et al., 2024）上的一篇论文用到的旭日图。题目：The Vibrio cholerae CBASS phage defence system modulates resistance and killing by antifolate antibiotics. https://doi.org/10.1038/s41564-023-01556-y
图 1 | 研究中测试的化合物库的组成。
化合物按目标（在抗菌药物的情况下，内环）和化合物类别（外环）进行分类。
结果
文中试图通过评估野生型（WT）霍乱弧菌和CBASS操纵子缺失（ΔCBASS）菌株在94种小分子（包括抗生素、人类药物、人类内源性代谢产物和食品添加剂）存在下的细菌生长，系统地研究CBASS对抗微生物活性的影响（图1b和补充表1）。
源代码及测试数据链接：
https://github.com/YongxinLiu/MicrobiomeStatPlot/
或公众号后台回复“MicrobiomeStatPlot”领取
软件包安装
# 基于CRAN安装R包，检测没有则安装p_list = c("dplyr", "ggplot2", "formattable")for(p in p_list){if (!requireNamespace(p)){install.packages(p)}library(p, character.only = TRUE, quietly = TRUE, warn.conflicts = FALSE)}# 加载R包 Load the packagesuppressWarnings(suppressMessages(library(dplyr)))suppressWarnings(suppressMessages(library(ggplot2)))
实战
绘制饼图
参考：
https://mp.weixin.qq.com/s/xUQM-1h-OeeWGjJlRw3d_g
# 构建数据# Load datacount_data <- data.frame(class = c("1st", "2nd", "3rd", "Crew"),n = c(325, 285, 706, 885),prop = c(14.8, 12.9, 32.1, 40.2))# 计算标签位置# Label positionscount_data <- count_data %>%arrange(desc(class)) %>%mutate(lab_ypos = cumsum(prop) - 0.5 * prop)# 使用ColorBrewer中的调色板# Set colormycols <- c("#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3")# 绘制的饼图# Pie plotp_pie1 <- ggplot(count_data, aes(x = "", y = prop, fill = class)) +geom_bar(width = 1, stat = "identity", color = "black", size = 0.5) +coord_polar("y", start = pi/4) +geom_text(aes(y = lab_ypos, label = paste0(prop, "%")), color = "black", size = 3.5) +scale_fill_manual(values = mycols) +theme_void() +theme(legend.position = "right")# 绘制空心饼图（甜甜圈图）# Draw a hollow pie chart (donut chart)p_pie2 <- ggplot(count_data, aes(x = 2, y = prop, fill = class)) +geom_bar(stat = "identity", color = "black", size = 0.5) +coord_polar(theta = "y", start = pi/4) +geom_text(aes(y = lab_ypos, label = paste0(prop, "%")), color = "black", size = 3.5) +scale_fill_manual(values = mycols) +theme_void() +xlim(1, 3) +theme(legend.position = "right")ggsave('results/donut_chart.pdf', p_pie2)
使用ggplot2包作图
参考：
https://mp.weixin.qq.com/s/19clA4xZqoAl7KuY96ZJjQ?search_click_id=9261072915409092102-1714444702544-1010392356
# 加载数据# Load datadf <- read.table("data/data.txt", header = TRUE, check.names = FALSE, sep = "\t")# 定义百分比转换函数# Define percentage conversion functionconvert_to_percent <- function(x) {return(paste0(round(x * 100, 1), "%"))}# 分别计算group1、group2、group3的数据# Calculate the data of group1, group2, and group3 respectivelyget_data <- function(group_col, data) {data_group <- aggregate(value ~ get(group_col), data, sum)data_group$Rel <- data_group$value / sum(data_group$value)data_group$per <- convert_to_percent(data_group$Rel)colnames(data_group)[1] <- group_coldata_group <- data_group %>%mutate(ymax = cumsum(Rel),ymin = c(0, head(ymax, -1)),labelposition = (ymax + ymin) / 2)return(data_group)}data1 <- get_data("group1", df)data2 <- get_data("group2", df)data3 <- get_data("group3", df)# 设定颜色# Set colormycolors1 <- c("#66c2a5", "#fc8d62", "#8da0cb", "#e78ac3", "#a6d854")mycolors2 <- c("#ffd92f", "#e5c494", "#b3b3b3")mycolors3 <- c("#e41a1c", "#377eb8")# 绘制第一个圆环图# Plot First circlep1 <- ggplot(data1, aes(ymax = ymax, ymin = ymin, xmax = 3, xmin = 2)) +geom_rect(aes(fill = group1), color = "white") +geom_text(aes(x = 2.5, y = labelposition, label = paste0(group1, "\n(", per, ")")),size = 4, color = "black") +coord_polar(theta = "y") +theme_void() +scale_fill_manual(values = mycolors1) +theme(legend.position = "none")#p1# 增加中间空白区域# Add the blank spacep2 <- p1 + ylim(0, 1.1)#p2# 绘制双环图（内环 + 外环）# Draw a double ring plot (inner ring + outer ring)p3 <- ggplot() +geom_rect(data = data2, aes(ymax = ymax, ymin = ymin, xmax = 2, xmin = 0, fill = group2), color = "white") +geom_rect(data = data1, aes(ymax = ymax, ymin = ymin, xmax = 3.5, xmin = 2, fill = group1), color = "white", alpha = 0.6) +geom_text(data = data2, aes(x = 1, y = labelposition, label = paste0(group2, "\n(", per, ")")),size = 4, color = "black") +geom_text(data = data1, aes(x = 2.75, y = labelposition, label = paste0(group1, "\n(", per, ")")),size = 3, color = "black") +coord_polar(theta = "y") +theme_void() +scale_fill_manual(values = c(mycolors2, mycolors1)) +theme(legend.position = "none") +xlim(0, 3.5)#p3# 增加空白区域# Add the blank spacep4 <- p3 + ylim(0, 1.1)#p4# 绘制三环旭日图# Draw a three-ring sunburst plotp5 <- ggplot() +geom_rect(data = data3, aes(ymax = ymax, ymin = ymin, xmax = 2, xmin = 0, fill = group3), color = "white") +geom_rect(data = data2, aes(ymax = ymax, ymin = ymin, xmax = 3.5, xmin = 2, fill = group2), color = "white", alpha = 0.6) +geom_rect(data = data1, aes(ymax = ymax, ymin = ymin, xmax = 5, xmin = 3.5, fill = group1), color = "white", alpha = 0.3) +geom_text(data = data3, aes(x = 1, y = labelposition, label = paste0(group3, "\n(", per, ")")),size = 3.5, color = "black") +geom_text(data = data2, aes(x = 2.75, y = labelposition, label = paste0(group2, "\n(", per, ")")),size = 3, color = "black") +geom_text(data = data1, aes(x = 4.25, y = labelposition, label = paste0(group1, "\n(", per, ")")),size = 3, color = "black") +coord_polar(theta = "y") +theme_void() +scale_fill_manual(values = c(mycolors3, mycolors2, mycolors1)) +theme(legend.position = "none") +xlim(0, 5)#p5# 增加空白区域# Add the blank spacep6 <- p5 + ylim(0, 1.1)#p6ggsave('results/Three_ring_sunburst_plot.pdf', p6)
排版combo plots
library(cowplot)width = 89height = 59p0 = plot_grid(p_pie1 ,p_pie2, p1, p2, p3, p4, p5, p6,labels = c("A", "B", "C", "D", "E", "F", "G", "H"), ncol = 4)ggsave("results/SunBurst_plot01.pdf", p0, width = width * 3, height = height * 3, units = "mm")
使用此脚本，请引用下文：
Yong-Xin Liu, Lei Chen, Tengfei Ma, Xiaofang Li, Maosheng Zheng, Xin Zhou, Liang Chen, Xubo Qian, Jiao Xi, Hongye Lu, Huiluo Cao, Xiaoya Ma, Bian Bian, Pengfan Zhang, Jiqiu Wu, Ren-You Gan, Baolei Jia, Linyang Sun, Zhicheng Ju, Yunyun Gao, Tao Wen, Tong Chen. 2023. EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research. iMeta 2: e83. https://doi.org/10.1002/imt2.83
Copyright 2016-2024 Defeng Bai baidefeng@caas.cn, Chuang Ma 22720765@stu.ahau.edu.cn, Jiani Xun 15231572937@163.com, Yong-Xin Liu liuyongxin@caas.cn
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