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R语言可视化学习笔记之ggridges包

已有 3330 次阅读 2019-10-28 19:38 |个人分类:生物信息|系统分类:科研笔记

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布局教程来了!!

ggplot2学习笔记之图形排列

R包ggseqlogo |置换序列分析图

ggplot2高效实用指南(可视化脚本,工具,套路,配色)

简介

ggridges。主要包用来绘制山峦图产品尤其的英文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:

  • geom_ridgeline():主要放置山脊线图

  • geom_density_ridges():主要布局密度山脊线图

具体用法可以参考官方文档:

https://cran.r-project.org/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制,此时美学映射height没有必要编写函数中。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())

环尺度

为了使ggridges 重新呈现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,作者提供了循环比例尺作为颜色轮转映射。

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,周期性尺度为了防止误解是不安排图例的,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)


ggplot2一样,图例是可以修改的,其他参数尺寸大小,宽度,形状等都是可以通过循环刻度进行修改。

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.r-project.org/web/packages/ggridges/vignettes/introduction.html和https://cran.r-project.org/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?

如果不知道,可能你需要来参加单细胞转录组的课程了!!!




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