作图R包（base、ggplot2、ggpubr）
拼图函数、R包（par里的mfrow、grid.arrange、cowplot、customLayout、patchwork）
导出（1.经典三段论；2.ggsave；3.eoffice-topptx）

一、基础包-绘图函数（了解）

基础包.png

二、ggplot2（重点）

语法及代码

1.入门级绘画模版

  1. ggplot(data = iris)+
  2.   geom_point(mapping = aes(x = Sepal.Length,
  3.                            y = Petal.Length))
  4. theme_class()#去掉网格和灰色背景
  5. theme_bw()#留下网格，去掉灰色背景
  6. ###以geom开头的画图函数
  7. ###ggplot2的特殊语法：列名不带引号，行末写加号

2.映射

#2.属性设置（颜色、大小、透明度、点的形状，线型等）

#2.1 手动设置，需要设置为有意义的值

ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length), 
             color = "blue")

ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length), 
             size = 5,     # 点的大小5mm
             alpha = 0.5,  # 透明度 50%
             shape = 8)  # 点的形状

#2.2 映射：按照数据框的某一列来定义图的某个属性
ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species))

## Q1 能不能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"))###换成shape、size也可

## Q2 区分color和fill两个属性
### Q2-1 空心形状和实心形状都用color设置颜色
ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species),
             shape = 17) #17号，实心的例子

ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species),
             shape = 2) #2号，空心的例子
### Q2-2 既有边框又有内心的，才需要color和fill两个参数(color修改边框，fill填充)

ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species),
             shape = 24,
             fill = "black") #24号，双色的例子

形状.png
颜色.png

3.分面

单分面
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)

4.几何对象

局部设置和全局设置

ggplot(data = iris) + 
  geom_smooth(mapping = aes(x = Sepal.Length, 
                          y = Petal.Length))+
  geom_point(mapping = aes(x = Sepal.Length, 
                           y = Petal.Length))

ggplot(data = iris,mapping = aes(x = Sepal.Length, y = Petal.Length))+
  geom_smooth()+
  geom_point()

5.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
#5.1.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")
#5.2count改为prop(比例)
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, y = ..prop.., group = 1))

6.位置关系

# 6.1抖动的点图
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()###点分散在分布范围内

# 6.2堆叠直方图
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut,fill=clarity))

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

7.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()

三、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
library(ggpubr)
ggscatter(iris,x="Sepal.Length",
          y="Petal.Length",
          color="Species")

p <- ggboxplot(iris, x = "Species", 
               y = "Sepal.Length",
               color = "Species", 
               shape = "Species",
               add = "jitter")
p
my_comparisons <- list( c("setosa", "versicolor"), 
                        c("setosa", "virginica"), 
                        c("versicolor", "virginica") )
p + stat_compare_means(comparisons = my_comparisons)+ # Add pairwise comparisons p-value
  stat_compare_means(label.y = 9)

四、图片保存与导出

ggplot2系列：

ggsave("iris_box_ggpubr.png")
ggsave(p, filename = "iris_box_ggpubr.png")

三段论：
1.pdf.(“test.pdf”)
2.作图代码
3.dev.off

五、拼图—patchwork

六、其他

1.代码可运行却不出图-因为画板被占用:dev.off;dev.new
2.STHDA作图代码网站

代码及图片均来自于生信技能树小洁老师