其他
gghalves包-你五毛我五毛
介绍
gghalves可以通过ggplot2轻松地编写自己想要的一半一半（half-half plots）的图片。比如：在散点旁边显示箱线图、在小提琴图旁边显示点图。
gghalves[1]将_half_扩展添加到选定的geom。比如：geom_half_violin()函数，相当于geom_violin()函数的变体，该函数主要作用就是展示一半的小提琴图，然后与其他图形组合。还包含以下函数：
geom_half_boxplot geom_half_violin geom_half_point
安装
gghalves通过GitHub安装:
if (!require(devtools)) {
install.packages('devtools')
}
devtools::install_github('erocoar/gghalves')
函数介绍
geom_half_violin(mapping = NULL, data = NULL, stat = "half_ydensity",
position = "dodge", ..., side = "l", nudge = 0,
draw_quantiles = NULL, trim = TRUE, scale = "area",
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
其参数包括：翻译来源生信玩家[2]
| 参数 | 解释 |
|---|---|
mapping | 通过aes()指定图形属性映射。默认为NULL，使用ggplot()中aes()指定的映射。 |
data | 指定数据框。默认为NULL，使用ggplot()中的数据。 |
stat | 覆盖geom_density()和stat_density()之间的默认连接。 |
position | 位置调整，可以是字符串，默认为"dodge"，也可以是位置调整函数的调用结果。 |
side | 画半小提琴图的一侧。“ l”代表左，“ r”代表右，默认为“ l”。 |
nudge | 在小提琴图和分配给x轴上给定因子的空间中间之间添加空间。 |
draw_quantiles | 如果不是MULL（默认为NULL），在给定的密度估计分位数处绘制水平线。 |
trim | 若为TRUE（默认），将小提琴的尾部修整到数据范围。若为FALSE，不修剪尾巴。 |
scale | 如果为"area"（默认），则所有小提琴都具有相同的面积（修剪尾部之前）。 |
na.rm | 如果为FALSE（默认），则会使用警告删除缺失值。如果为TRUE，则会自动删除缺少的值。 |
show.legend | 逻辑值，默认为NA，若为FALSE，不显示该图层的图例； 若为TRUE，则显示该图层的图例。 它也可以是带有名称（图形属性）的逻辑向量，用来选择要显示的图形属性。如show.legend = c(size = TRUE,color = FALSE)表示显示size对应的图例，而不显示color对应的图例。 |
inherit.aes | 默认为TRUE，若为FALSE，覆盖ggplot()中aes()默认属性，而不是与他们组合。 |
geom | 覆盖geom_density()和stat_density()之间的默认连接。 |
bw | 要使用的平滑带宽度。如果是数字，则为平滑内核的标准差。 |
adjust | 多次带宽调整。这使得可以在仍使用带宽估计器的情况下调整带宽。例如，adjust = 1/2表示使用默认带宽的一半。 |
示例
单个函数
我们以iris数据集作为本例数据，先使用单个函数进行绘制。
if (!require(devtools)) {
install.packages('devtools')
}
devtools::install_github('erocoar/gghalves')
geom_half_boxplot
library(gghalves)
ggplot(iris, aes(x = Species, y = Petal.Width, fill = Species)) +
geom_half_boxplot()
默认为箱子在右，使用center = TRUE将箱子居中。下面函数参数调整类似，就不再绘制结果了，就把最原始的进行展示。
ggplot(iris, aes(x = Species, y = Petal.Width, fill = Species)) +
geom_half_boxplot(center = TRUE)
geom_half_violin
ggplot(iris, aes(x = Species, y = Petal.Width, fill = Species)) +
geom_half_violin()
geom_half_point
ggplot(iris, aes(x = Species, y = Petal.Width, fill = Species)) +
geom_half_point()
综合案例
云雨图
该案例来自官网案例，但并没有对代码进行解释。这里小编对代码进行详细解释，喜欢的伙伴，可以按照解释自己理解，并用到自己实际所需的复合图中。
先将数据的统计摘要进行计算存到了summ_iris中，包含了均值，标准差，数量标准误差。iris_plot为所需数据，这里将Species变量设置为因子，因为要用它作为分类变量。
library(tidyverse)
# 统计摘要
summ_iris <- iris %>%
group_by(Species) %>%
summarise(
mean = mean(Sepal.Length),
sd = sd(Sepal.Length),
n = n()
) %>%
mutate(se = sd/sqrt(n),
Species = factor(Species, levels = c('versicolor', 'setosa', 'virginica')))
summ_iris
## # A tibble: 3 x 5
## Species mean sd n se
## <fct> <dbl> <dbl> <int> <dbl>
## 1 setosa 5.01 0.352 50 0.0498
## 2 versicolor 5.94 0.516 50 0.0730
## 3 virginica 6.59 0.636 50 0.0899
# 数据转换
iris_plot <- iris %>%
mutate(Species = factor(Species, levels = c('versicolor', 'setosa', 'virginica')))
head(iris_plot)
接下来进行绘图，我们想要得到Species与Sepal.Length的关系，其中Species为离散变量，Sepal.Length为连续变量。并绘制了半边的小提琴图，并将该图往右移了0.15，上下位置不变（position_nudge(x = .15, y = 0)），为了后面绘制其他图形留位置。
library(gghalves)
library(ggsignif)
library(ggsci)
library(ggpubr)
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
side = 'r')
接下来加入散点图，并使x坐标往左移动0.1（x = as.numeric(Species)-0.1），使用position_jitter使得重复的点分散开。
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
side = 'r') +
geom_point(aes(x = as.numeric(Species)-0.1,
y = Sepal.Length,color = Species),
position = position_jitter(width = .05),size = .25, shape = 20)
在原来基础上加入箱子图，位置放在正中间
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
adjust=1.5, trim=FALSE, colour=NA, side = 'r') +
geom_point(aes(x = as.numeric(Species)-0.1,
y = Sepal.Length,color = Species),
position = position_jitter(width = .05),size = .25, shape = 20) +
geom_boxplot(aes(x = Species,y = Sepal.Length, fill = Species),
outlier.shape = NA,
width = .05,
color = "black")
这里比较有趣的是，作者还通过geom_point和geom_errorbar加入和汇总信息以及对应的误差项。
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
adjust=1.5, trim=FALSE, colour=NA, side = 'r') +
geom_point(aes(x = as.numeric(Species)-0.1,
y = Sepal.Length,color = Species),
position = position_jitter(width = .05),size = .25, shape = 20) +
geom_boxplot(aes(x = Species,y = Sepal.Length, fill = Species),
outlier.shape = NA,
width = .05,
color = "black")+
geom_point(data=summ_iris,
aes(x=Species,y = mean,group = Species, color = Species),
shape=18,
size = 1.5,
position = position_nudge(x = .1,y = 0)) +
geom_errorbar(data = summ_iris,
aes(x = Species, y = mean, group = Species, colour = Species,
ymin = mean-se, ymax = mean+se),
width=.05,
position=position_nudge(x = .1, y = 0)
)
使用ggsci包的scale_color_aaas(),scale_fill_aaas()将尺度的颜色进行改变（非常好用！)在下面展示另外一种配色（scale_color_jco）
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
adjust=1.5, trim=FALSE, colour=NA, side = 'r') +
geom_point(aes(x = as.numeric(Species)-0.1,
y = Sepal.Length,color = Species),
position = position_jitter(width = .05),size = .25, shape = 20) +
geom_boxplot(aes(x = Species,y = Sepal.Length, fill = Species),
outlier.shape = NA,
width = .05,
color = "black")+
geom_point(data=summ_iris,
aes(x=Species,y = mean,group = Species, color = Species),
shape=18,
size = 1.5,
position = position_nudge(x = .1,y = 0)) +
geom_errorbar(data = summ_iris,
aes(x = Species, y = mean, group = Species, colour = Species,
ymin = mean-se, ymax = mean+se),
width=.05,
position=position_nudge(x = .1, y = 0)
) +
scale_color_aaas() +
scale_fill_aaas()
最后使用ggpubr包的geom_signif加入显著性结果，ggsave保存图片。
# 绘图
ggplot(iris_plot , aes(x = Species, y = Sepal.Length, fill = Species))+
geom_half_violin(aes(fill = Species),
position = position_nudge(x = .15, y = 0),
adjust=1.5, trim=FALSE, colour=NA, side = 'r') +
geom_point(aes(x = as.numeric(Species)-0.1,
y = Sepal.Length,color = Species),
position = position_jitter(width = .05),size = .25, shape = 20) +
geom_boxplot(aes(x = Species,y = Sepal.Length, fill = Species),
outlier.shape = NA,
width = .05,
color = "black")+
geom_point(data=summ_iris,
aes(x=Species,y = mean,group = Species, color = Species),
shape=18,
size = 1.5,
position = position_nudge(x = .1,y = 0)) +
geom_errorbar(data = summ_iris,
aes(x = Species, y = mean, group = Species, colour = Species,
ymin = mean-se, ymax = mean+se),
width=.05,
position=position_nudge(x = .1, y = 0)
) +
scale_color_jco() +
scale_fill_jco() +
geom_signif(comparisons = list(c("versicolor", "setosa"),
c("versicolor", "virginica"),
c("setosa", "virginica")),
y_position = c(8.2, 8.6, 8.4),
map_signif_level = c("***" = 0.001, "**" = 0.01, "*" = 0.05)) +
ggsave('云雨图.pdf', width = 6, height = 8)
混合图
最后是混合图，根据自己想要的图，可以自行添加。相信这个代码简单的图给大家学术作图上省了不少时间。
library(tidyverse)
ggplot() +
geom_half_boxplot(
data = iris %>% filter(Species=="setosa"),
aes(x = Species, y = Sepal.Length, fill = Species), outlier.color = NA) +
ggbeeswarm::geom_beeswarm(
data = iris %>% filter(Species=="setosa"),
aes(x = Species, y = Sepal.Length, fill = Species, color = Species), beeswarmArgs=list(side=+1)
) +
geom_half_violin(
data = iris %>% filter(Species=="versicolor"),
aes(x = Species, y = Sepal.Length, fill = Species), side="r") +
geom_half_dotplot(
data = iris %>% filter(Species=="versicolor"),
aes(x = Species, y = Sepal.Length, fill = Species), method="histodot", stackdir="down") +
geom_half_boxplot(
data = iris %>% filter(Species=="virginica"),
aes(x = Species, y = Sepal.Length, fill = Species), side = "r", errorbar.draw = TRUE,
outlier.color = NA) +
geom_half_point(
data = iris %>% filter(Species=="virginica"),
aes(x = Species, y = Sepal.Length, fill = Species, color = Species), side = "l") +
scale_fill_manual(values = c("setosa" = "#cba1d2", "versicolor"="#7067CF","virginica"="#B7C0EE")) +
scale_color_manual(values = c("setosa" = "#cba1d2", "versicolor"="#7067CF","virginica"="#B7C0EE")) +
theme(legend.position = "none") +
ggsave('综合图.pdf', width = 6, height = 8)
其他参考资料
Using gghalves--Frederik Tiedemann[3]
gghalves: Compose Half-Half Plots Using Your Favourite Geoms[4]
CRAN[5]
参考资料
gghalves: https://github.com/erocoar/gghalves
[2]生信玩家: https://blog.csdn.net/weixin_43700050/article/details/107512448
[3]Using gghalves--Frederik Tiedemann: https://erocoar.github.io/gghalves/
[4]gghalves: Compose Half-Half Plots Using Your Favourite Geoms: https://cran.r-project.org/web/packages/gghalves/index.html
[5]CRAN: https://rdrr.io/cran/gghalves/f/vignettes/gghalves.Rmd