vioplot--一行代码搞定小提琴图

作图丫

发布于 2022-03-29 09:15:38

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发布于 2022-03-29 09:15:38

文章被收录于专栏：作图丫

导语

GUIDE ╲

小提琴图是帮助研究人员可视化数据的强大工具，尤其是在分析的质量检查和探索部分，小提琴图比箱线图更灵活地绘制变化。

背景介绍

小提琴图是箱线图和密度图的组合。今天小编给大家带来的R包vioplot，允许我们使用简单的代码对小提琴图进行个性化的绘制。

R包安装

BiocManager::install("vioplot")
library(vioplot)

可视化介绍

小提琴图和箱线图的比较

首先用同样的数据集绘制两种图形

data(iris)
boxplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"))
vioplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"))

我们可以看到小提琴图能够明显的展示数据的分布情况，这是箱线图所不具备的。

参数设置

我们可以看到默认的颜色可能比较单调，所以我们可以自行定义绘图颜色。

vioplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"), main = "Sepal Length", col="lightblue")

对于分组数据：

vioplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"), main = "Sepal Length", col=c("lightgreen", "lightblue", "palevioletred"))
legend("topleft", legend=c("setosa", "versicolor", "virginica"), fill=c("lightgreen", "lightblue", "palevioletred"), cex = 0.5)

也可以使用 col 和 border 参数分别为小提琴填充和边框自定义颜色：

vioplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"), main = "Sepal Length", col="lightblue", border="royalblue")

矢量化

这些颜色和形状设置也可以为每个小提琴单独定制：

vioplot(iris$Sepal.Length[iris$Species=="setosa"], iris$Sepal.Length[iris$Species=="versicolor"], iris$Sepal.Length[iris$Species=="virginica"], names=c("setosa", "versicolor", "virginica"), main="Sepal Length (Equal Area)", areaEqual = T, col=c("lightgreen", "lightblue", "palevioletred"), border=c("darkolivegreen4", "royalblue4", "violetred4"), rectCol=c("forestgreen", "blue", "palevioletred3"), lineCol=c("darkolivegreen", "royalblue", "violetred4"), colMed=c("green", "cyan", "magenta"), pchMed=c(15, 17, 19))

可以用于比较的split violin plot

iris_large <- iris[iris$Sepal.Width > mean(iris$Sepal.Width), ]
iris_small <- iris[iris$Sepal.Width <= mean(iris$Sepal.Width), ]
vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line", side = "right")
vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line", side = "left", add = T)
title(xlab = "Species", ylab = "Sepal Length")
legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Sepal Width")