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作者：严涛 浙江大学作物遗传育种在读研究生（生物信息学方向）伪码农，R语言爱好者，爱开源。 严涛老师的绘图教程还有： gganimate |诺奖文章里面的动图绘制教程来了！！
ggplot2学习笔记之图形排列
R包ggseqlogo |绘制序列分析图 ggplot2高效实用指南 (可视化脚本、工具、套路、配色) 简介ggridges包主要用来绘制山峦图。尤其是针对时间或者空间分布可视化具有十分好的效果。ggridges主要提供两个几何图像函数： 具体用法可以参考官方文档： https://cran./web/packages/ggridges/vignettes/introduction.html geom_ridgeline()library(ggridges)
library(tidyverse)
# grid.arrange来自于gridExtra包，可以同时拼图多个ggplot2对象
library(gridExtra)
my_data <- data.frame(x=1:5, y=rep(1,5), height=c(0,1,-1,3,2))
plot_base <- ggplot(my_data, aes(x, y, height=height))
# 默认负值不显示，除非指定min_height参数
grid.arrange(plot_base+geom_ridgeline(),
plot_base+geom_ridgeline(min_height=-2), ncol=2)
geom_density_ridges()geom_density_ridges()函数首先会根据数据计算密度然后绘图，此时美学映射height没有必要写入函数中。下面使用lincoln_weather数据集。 # creates a vector of n equally spaced colors along the
# Matplolib 'viridis' color map
# also designed to be perceived by readers with the most common form of color blindness
# scale_fill_viridis函数来源于此包，
# 其参数 option用于设置颜色 'magma' (or 'A'), 'inferno' (or 'B'), 'plasma' (or 'C'),
and 'viridis' (or 'D', the default option).
# ?viridis可以查看其具体含义
library(viridis)
head(lincoln_weather[ ,1:4])
## # A tibble: 6 x 4
## CST `Max Temperature [F]` `Mean Temperature [F]` `Min Temperature ~
## <chr> <int> <int> <int>
## 1 2016-1-1 37 24 11
## 2 2016-1-2 41 23 5
## 3 2016-1-3 37 23 8
## 4 2016-1-4 30 17 4
## 5 2016-1-5 38 29 19
## 6 2016-1-6 34 33 32
# x后的值用 ` (反引号)括起，是因为列名字中存在空格和特殊字符，需要特殊对待
# fill = ..x..， double dots是ggplot2的一种特殊识别符，用来区分定义的和计算的美学参数
# 这里指用横轴的数据着色
ggplot(lincoln_weather, aes(x=`Mean Temperature [F]`, y=`Month`, fill=..x..))+
geom_density_ridges_gradient(scale=3, rel_min_height=0.01, gradient_lwd = 1.)+
scale_x_continuous(expand = c(0.01, 0))+ # 扩展下横轴和纵轴
scale_y_discrete(expand = c(0.01,0))+
scale_fill_viridis(name='Temp. [F]', option = 'C')+
labs(title='Temperature in Lincoln NE',
subtitle='Mean temperature (Fahrenheit) by month for 2016\nData:Orogin CSV from the Weather Underground ')+
theme_ridges(font_size = 13, grid = FALSE)+
theme(axis.title.y = element_blank())
cyclinal scales为了使得ggridges绘制的图形可视化效果最好，同时为了减少用户对颜色设置的困难，作者提供了cyclinal scales用于颜色轮转映射。 ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
geom_density_ridges(scale=4)+
scale_fill_cyclical(values = c('blue', 'green'))+
theme_ridges(grid = FALSE)
默认的，cyclinal scales为了防止误解是不绘制图例的，但是可以通过选项guide='legend'添加图例。 ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
geom_density_ridges(scale=4)+
scale_fill_cyclical(values = c('blue', 'green'), guide='legend')+
theme_ridges(grid = FALSE)
跟ggplot2一样，图例是可以修改的,其他参数比如大小、透明度、形状等都是可以通过cyclinal scales修改。 ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
geom_density_ridges(scale=4)+
scale_fill_cyclical(values = c('blue', 'green'), guide='legend',
labels=c('Fair'='blue', 'Good'='green'),
name='Fill colors')+
theme_ridges(grid = FALSE)
再来2个示例不做解释了，如果想重现就把代码拆解开，按需修改。一句句话单独拆开运行，理解其操作内容。 library(dplyr)
library(forcats)
Catalan_elections %>%
mutate(YearFct = fct_rev(as.factor(Year))) %>%
ggplot(aes(y = YearFct)) +
geom_density_ridges(
aes(x = Percent, fill = paste(YearFct, Option)),
alpha = .8, color = 'white', from = 0, to = 100
) +
labs(
x = 'Vote (%)',
y = 'Election Year',
title = 'Indy vs Unionist vote in Catalan elections',
subtitle = 'Analysis unit: municipalities (n = 949)',
caption = 'Marc Belzunces (@marcbeldata) | Source: Idescat'
) +
scale_y_discrete(expand = c(0.01, 0)) +
scale_x_continuous(expand = c(0.01, 0)) +
scale_fill_cyclical(
breaks = c('1980 Indy', '1980 Unionist'),
labels = c(`1980 Indy` = 'Indy', `1980 Unionist` = 'Unionist'),
values = c('#ff0000', '#0000ff', '#ff8080', '#8080ff'),
name = 'Option', guide = 'legend'
) +
theme_ridges(grid = FALSE)
library(DAAG) # for ais dataset
ais$sport <- factor(
ais$sport,
levels = c('B_Ball', 'Field', 'Gym', 'Netball', 'Row', 'Swim', 'T_400m', 'T_Sprnt', 'Tennis', 'W_Polo'),
labels = c('Basketball', 'Field', 'Gym', 'Netball', 'Row', 'Swim', 'Track 400m', 'Track Sprint', 'Tennis', 'Water Polo')
)
ggplot(ais, aes(x=ht, y=sport, color=sex, point_color=sex, fill=sex)) +
geom_density_ridges(
jittered_points=TRUE, scale = .95, rel_min_height = .01,
point_shape = '|', point_size = 3, size = 0.25,
position = position_points_jitter(height = 0)
) +
scale_y_discrete(expand = c(.01, 0)) +
scale_x_continuous(expand = c(0, 0), name = 'height [cm]') +
scale_fill_manual(values = c('#D55E0050', '#0072B250'), labels = c('female', 'male')) +
scale_color_manual(values = c('#D55E00', '#0072B2'), guide = 'none') +
scale_discrete_manual('point_color', values = c('#D55E00', '#0072B2'), guide = 'none') +
guides(fill = guide_legend(
override.aes = list(
fill = c('#D55E00A0', '#0072B2A0'),
color = NA, point_color = NA))
) +
ggtitle('Height in Australian athletes') +
theme_ridges(center = TRUE)
还有很多用法有兴趣的可以查看官方文档https://cran./web/packages/ggridges/vignettes/introduction.html和https://cran./web/packages/ggridges/vignettes/gallery.html）继续学习。 那你知道单细胞基因表达中这个图怎么画了吗？
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