棒棒糖图与哑铃图（Julia）

作者

[编辑] 王诗翔

[贡献] Claude Code —— AI 生成，独立 AI 复核；

修改于

2026-10-19

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棒棒糖图用细线加端点圆点替代条形图的条形，在保持排序可读性的同时大幅削减图形墨量；哑铃图把每行两个圆点用线段连接，直观呈现两个条件间的变化。在生物医学研究中，棒棒糖图常用于富集条目或效应量排序，哑铃图用于逐特征比较两个队列或处理臂。二者均由 CairoMakie 的 hlines!/vlines! 与 scatter! 组合而成。

示例

环境配置

  • 系统要求：跨平台（Linux/MacOS/Windows）
  • 编程语言：Julia
  • 依赖包：CairoMakie、DataFrames、Statistics 
using CairoMakie
using DataFrames
using Statistics
using Random

数据准备

我们模拟一个通路富集结果（基因集的 −log10 校正 p 值）和一张用于哑铃图的两条件差异表达表。

pathways = ["T cell activation", "Antigen processing", "IFN-gamma response",
            "IL-6/JAK/STAT3", "TNF-alpha signaling", "Oxidative phosphorylation",
            "Fatty acid metabolism", "DNA repair", "Apoptosis", "mTORC1 signaling"]
enrichment = DataFrame(Pathway = pathways,
                       NegLogFDR = [7.8, 6.4, 5.9, 4.7, 4.1, 3.2, 2.8, 2.1, 1.6, 1.2])
sort!(enrichment, :NegLogFDR)

dumbbell = DataFrame(Gene = ["CD274", "IFIT1", "CXCL10", "MKI67", "STAT1"],
                     Sham = [-0.3, 2.1, 2.8, 0.5, 1.9],
                     Treat = [1.4, 3.9, 4.6, -1.2, 3.3])
sort!(dumbbell, :Treat)
5×3 DataFrame
Row Gene Sham Treat
String Float64 Float64
1 MKI67 0.5 -1.2
2 CD274 -0.3 1.4
3 STAT1 1.9 3.3
4 IFIT1 2.1 3.9
5 CXCL10 2.8 4.6

可视化

横向棒棒糖图

每行为一条线段（hlines!）加一个标记（scatter!）；显著条目用颜色高亮并配阈值参考线。

y_pos = 1:nrow(enrichment)
sig = enrichment.NegLogFDR .>= 2
dot_colors = ifelse.(sig, :tomato, :gray70)

fig = Figure(size = (540, 400))
ax = Axis(fig[1, 1], xlabel = "-log\$_{10}\$ (adjusted p-value)")
hlines!(ax, y_pos; xmin = 0.0, xmax = enrichment.NegLogFDR,
        color = dot_colors, linewidth = 1.6)
scatter!(ax, enrichment.NegLogFDR, y_pos; color = dot_colors, markersize = 13)
vlines!(ax, [2]; color = :gray50, linestyle = :dash, linewidth = 0.9)
ax.yticks = (y_pos, enrichment.Pathway)
hidespines!(ax, :t, :r)
fig
图 1: 通路富集的横向棒棒糖图排序

纵向棒棒糖图

同样的构造用 vlines! 旋转为纵向，适合标签较短或幻灯片场景。

top8 = enrichment[end-7:end, :]

fig = Figure(size = (540, 380))
ax = Axis(fig[1, 1], ylabel = "-log\$_{10}\$ (adjusted p-value)")
x_pos = 1:nrow(top8)
vlines!(ax, x_pos; ymin = 0.0, ymax = top8.NegLogFDR,
        color = :steelblue, linewidth = 1.6)
scatter!(ax, x_pos, top8.NegLogFDR; color = :steelblue, markersize = 13)
ax.xticks = (x_pos, top8.Pathway)
ax.xticklabelrotation = 0.7
hidespines!(ax, :t, :r)
fig
图 2: 富集分数的纵向棒棒糖图

哑铃图

每个特征一条线段连接两个条件的值；两端圆点按条件着色，使变化的方向与幅度一目了然。

y = 1:nrow(dumbbell)

fig = Figure(size = (540, 380))
ax = Axis(fig[1, 1], xlabel = "log\$_{2}\$ fold change")
hlines!(ax, y; xmin = min.(dumbbell.Sham, dumbbell.Treat),
        xmax = max.(dumbbell.Sham, dumbbell.Treat),
        color = :gray70, linewidth = 2)
scatter!(ax, dumbbell.Sham, y; color = :steelblue, markersize = 13, label = "Sham")
scatter!(ax, dumbbell.Treat, y; color = :tomato, markersize = 13, label = "Treatment")
vlines!(ax, [0]; color = :gray40, linewidth = 0.9)
axislegend(ax; framevisible = false, position = :rb)
ax.yticks = (y, dumbbell.Gene)
hidespines!(ax, :t, :r)
fig
图 3: 比较两条件 log2 倍数变化的哑铃图

参考文献

  1. Makie development team. Makie.jl documentation — linesegments, scatter. https://docs.makie.org/stable/reference/plots/linesegments
  2. From Data to Viz. Lollipop plot. https://www.data-to-viz.com/graph/lollipop.html