跟小洁老师学习R语言的第六天

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贝诺酯

发布于 2023-03-16 16:40:48

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发布于 2023-03-16 16:40:48

文章被收录于专栏：在生信技能树学习在生信技能树学习

常用可视化R包

作图

base

ggplot2（特殊语法：列名不带引号，行末写加号）

颜色：color

大小：size

形状：shape

透明度：alpha

填充颜色：fill（既有边框又有内心的，才需要color和fill两个参数）

映射和手动设置的区别

自行指定映射的具体颜色

ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species))+
  scale_color_manual(values = c("blue","grey","red"))

分面

#分面
ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_wrap(~ Species)

#双分面
dat = iris
dat$Group = sample(letters[1:5],150,replace = T)
ggplot(data = dat) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_grid(Group ~ Species)

几何对象

几何对象可以叠加

#局部设置
ggplot(data = iris) + 
  geom_smooth(mapping = aes(x = Sepal.Length, 
                          y = Petal.Length))+
  geom_point(mapping = aes(x = Sepal.Length, 
                           y = Petal.Length))
#全局设置
ggplot(data = iris,mapping = aes(x = Sepal.Length, y = Petal.Length))+
  geom_smooth()+
  geom_point()

统计变换

View(diamonds)
table(diamonds$cut)

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut))

ggplot(data = diamonds) + 
  stat_count(mapping = aes(x = cut))

统计变换使用场景

#不统计，数据直接做图
fre = as.data.frame(table(diamonds$cut))
fre

ggplot(data = fre) +
  geom_bar(mapping = aes(x = Var1, y = Freq), stat = "identity")
#count改为prop（比例）
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, y = ..prop.., group = 1))

位置关系

ggplot(data = iris,mapping = aes(x = Species, 
                                 y = Sepal.Width,
                                 fill = Species)) + 
  geom_boxplot()+
  geom_point()

ggplot(data = iris,mapping = aes(x = Species, 
                                 y = Sepal.Width,
                                 fill = Species)) + 
  geom_boxplot()+
  geom_jitter()

# 堆叠直方图
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut,fill=clarity))

#  并列直方图
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")

坐标系

#翻转coord_flip()

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot() +
  coord_flip()
#极坐标系coord_polar()
bar <- ggplot(data = diamonds) + 
  geom_bar(
    mapping = aes(x = cut, fill = cut), 
    width = 1
  ) + 
  theme(aspect.ratio = 1) +
  labs(x = NULL, y = NULL)
bar
bar + coord_flip()
bar + coord_polar()

ggpubr

ggpubr 搜代码直接用，基本不需要系统学习

sthda上有大量ggpubr出的图

#1.基础包 略显陈旧 了解一下
plot(iris[,1],iris[,3],col = iris[,5]) 
text(6.5,4, labels = 'hello')

#2.ggplot2 中坚力量，语法有个性
library(ggplot2)
ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species))

#3.ggpubr 新手友好型 ggplot2简化和美化 褒贬不一
library(ggpubr)
ggscatter(iris,
          x="Sepal.Length",
          y="Petal.Length",
          color="Species")

拼图

par里的mfrow

grid.arrange

cowplot

customLayout

patchwork

导图

经典三段论

pdf("iris_box_ggpubr.pdf")
boxplot(iris[,1]~iris[,5])
text(6.5,4, labels = 'hello')
dev.off()#关闭画板

ggsave

p <- ggboxplot(iris, x = "Species", 
               y = "Sepal.Length",
               color = "Species", 
               shape = "Species",
               add = "jitter")
ggsave(p,filename = "iris_box_ggpubr.png")