BioF3 FigCode · SCI 绘图代码集

树状图（Treemap）

导出日期：2026年6月27日

分类：功能富集｜ 依赖包：treemap

解决的生物学问题

富集到的几十个 GO term 按"父类"汇总后，哪些大类占主导？

应用场景

GO BP/MF/CC 三大类占比
KEGG 通路类别汇总
突变频谱分类展示
基金分类资金占比

输入数据格式

层级数据框：parent, child, value

关键参数

index = c(parent, child) 嵌套层级
vSize = 数值列
palette / type = "categorical"
fontsize.labels 字号

快速开始

1. 直接在线运行

打开 FigCode 在线绘图，点击本工具卡片的"在线绘图"按钮即可用内置示例数据出图，零环境配置。

2. 本地复现

下载脚本和示例数据，本地 RStudio 运行：

# 下载
curl -O https://<your-site>/figcode/scripts/treemap.R
curl -O https://<your-site>/figcode/data/treemap.csv

3. 安装依赖

# CRAN 包
install.packages(c("treemap"))

# Bioconductor 包（如需）
# BiocManager::install(c())

完整代码

library(treemap)

# --- Demo: GO BP top categories ---
df <- data.frame(
  category = c(rep("Immune Response", 4),
               rep("Cell Cycle", 4),
               rep("Metabolism", 5),
               rep("Signal Transduction", 4),
               rep("Apoptosis", 3)),
  term = c(
    "T cell activation","B cell proliferation","Cytokine response","Interferon signaling",
    "Mitotic G1/S","Spindle checkpoint","DNA replication","Cytokinesis",
    "Lipid metabolism","Glycolysis","Amino acid","Cholesterol","Fatty acid oxidation",
    "MAPK","Wnt","TGFb","Hedgehog",
    "Caspase activation","BCL2 family","Mitochondrial apoptosis"
  ),
  count = c(45, 32, 28, 25,
            56, 42, 38, 30,
            48, 36, 33, 30, 28,
            52, 41, 35, 31,
            38, 30, 25)
)

treemap(
  df,
  index   = c("category", "term"),
  vSize   = "count",
  vColor  = "category",
  type    = "categorical",
  palette = c("#dc2626","#2563eb","#059669","#d97706","#7c3aed"),
  title   = "GO BP — Enrichment by Category",
  fontsize.labels = c(15, 9),
  fontcolor.labels = c("white","white"),
  border.col = "white",
  border.lwds = c(2, 1),
  align.labels = list(c("left","top"), c("center","center"))
)

替换为自己的数据

脚本中以 # --- Demo data --- 标注的段落是示例数据生成代码。替换为自己的数据时，保持列名一致即可：

输入格式：层级数据框：parent, child, value
使用 read.csv() / readRDS() 读取本地文件