从零开始的异世界生信学习 R语言部分 05 作图-1

#作图分三类

#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')

dev.off() #关闭画板

#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")

library(ggplot2)
#1.入门级绘图模板：作图数据，横纵坐标
ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length))

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"))
#color中的映射有多少个取值，manual应该就有几个颜色取值

## Q2 区分color和fill两个属性
##color是颜色，fill是填充颜色
### Q2-1 空心形状和实心形状都用color设置颜色（形状中1-20都不需要填充颜色）
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

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，填充颜色为黑色

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

#3.分面
ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_wrap(~ Species) 
##分面是根据数据的某一列把一张图分成若干的子图，根据列的取值分成若干的图
##用来分面的列：1.应该是分类变量，离散型数据；2.取值数量有限；

#双分面
dat = iris
dat$Group = sample(letters[1:5],150,replace = T)
ggplot(data = dat) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_grid(Group ~ Species)  #按照group列分隔行，species分隔列
  ##sample()函数表示随机取样
  ##dat$Group = sample(letters[1:5],150,replace = T) 表示在数据中新增了一列，其中按照内置数据letters（26个小写字母）中1-5（A-E）中可重复的取150个值

#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))  ##局部设置

ggplot(data = iris,mapping = aes(x = Sepal.Length, y = Petal.Length))+
  geom_smooth()+
  geom_point()  ##全局设置
##两种代码的图一样

#5.统计变换-直方图
View(diamonds)
table(diamonds$cut) ##内置数据钻石的切割质量

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut))  ##geom_bar函数默认没有y参数

ggplot(data = diamonds) + 
  stat_count(mapping = aes(x = cut))
## 图片的横坐标为钻石切割质量，纵坐标为每个取值的格式。作图只需要一列
## geom开头的几何对象函数，stat开头的几何变换函数，两种函数存在对应

#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，统计比例而不是具体数目，group参数表示分类统一比例
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, y = ..prop.., group = 1))

# 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()   ##jitter绘制抖动的点图

# 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")

#翻转coord_flip()

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot() +
  coord_flip()
##可以实现X轴，Y轴的转换

#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 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  ##ggplot2以及ggpubr绘制的图片可以进行赋值
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) 

ggplot(data = iris, mapping = aes(x = Species,
                                               y = Sepal.Width))+
  geom_violin(mapping = aes(fill = Species))+
  geom_boxplot()+
  geom_jitter(mapping = aes(shape = Species))+
  coord_flip()
#  也可以通过增加这个函数调整点图的点的形状 scale_shape_manual(values = c())
# 图层的叠放顺序取决于代码的顺序，先写的代码图片在最底下

#图片保存的三种方法

#1.基础包作图的保存
pdf("iris_box_ggpubr.pdf")
boxplot(iris[,1]~iris[,5])
text(6.5,4, labels = 'hello')
dev.off()

#2.ggplot系列图(包括ggpubr)通用的简便保存 ggsave
p <- ggboxplot(iris, x = "Species", 
               y = "Sepal.Length",
               color = "Species", 
               shape = "Species",
               add = "jitter")
ggsave(p,filename = "iris_box_ggpubr.png")
##保存的时候可以调节图片的参数，包括长宽以及像素，格式

#3.eoffice包 导出为ppt,全部元素都是可编辑模式
library(eoffice)
topptx(p,"iris_box_ggpubr.pptx")