ggplot2绘图学习 一文带你掌握如何添加各种bar

之前我们学习了ggplot绘制单变量，两个连续变量的图形，两个离散型变量。对于一个离散型变量，一个连续型变量，有很多作图方式，包括箱图，点图等等

· geom_boxplot() for box plot
· geom_violin() for violin plot
· geom_dotplot() for dot plot
· geom_jitter() for stripchart
· geom_line() for line plot
· geom_bar() for bar plot

今天我们介绍一下如何添加bar

先建立一个数据

library(tidyverse)# ToothGrowth data setdf <- ToothGrowthdf$dose <- as.factor(df$dose)head(df, 3)

通过dose分组，求每一组的len值得平均值和标准差

df2 <- df %>% group_by(dose) %>% summarise( sd = sd(len), len = mean(len) )head(df2)

构建图层

f <- ggplot(df2, aes(x = dose, y = len, ymin = len-sd, ymax = len+sd))

有不同种类的bar

Cross bar

f + geom_crossbar()# 颜色分组f + geom_crossbar(aes(color = dose))# 手动设置颜色f + geom_crossbar(aes(color = dose)) + scale_color_manual(values = c("#999999", "#E69F00", "#56B4E9"))+ theme_minimal()# 手动设置填充色f + geom_crossbar(aes(fill = dose)) + scale_fill_manual(values = c("#999999", "#E69F00", "#56B4E9"))+ theme_minimal()

多个分组

df3 <- df %>% group_by(supp, dose) %>% summarise( sd = sd(len), len = mean(len) )head(df3)

f <- ggplot(df3, aes(x = dose, y = len, ymin = len-sd, ymax = len+sd))f + geom_crossbar(aes(color = supp))# 使用 position_dodge()避免重叠f + geom_crossbar(aes(color = supp), position = position_dodge(1))

Error bar

f <- ggplot(df2, aes(x = dose, y = len))f + geom_errorbar(aes(color = dose,ymin = len-sd, ymax = len+sd), width = 0.2)# 加上连线f + geom_line(aes(group = 1)) +geom_errorbar(aes(color = dose,ymin = len-sd, ymax = len+sd), width = 0.2)
# 加上柱子f + geom_bar(aes(color = dose), stat = "identity", fill ="white") + geom_errorbar(aes(color = dose,ymin = len-sd, ymax = len+sd), width = 0.2)# 只保留上面一半的barf + geom_bar(aes(color = dose), stat="identity", fill ="white") + geom_errorbar(aes(color = dose,ymin = len, ymax = len+sd), width = 0.2)

多重分组的Error bar

f <- ggplot(df3, aes(x = dose, y = len))# 柱状图+Error barf +geom_errorbar(aes(color = supp,ymin = len-sd, ymax = len+sd),position = "dodge")+ geom_bar(aes(fill = supp), stat = "identity", position = "dodge")
# 线图+Error barf + geom_line(aes(group = supp, color = supp)) + geom_errorbar(aes(color = supp,ymin = len-sd, ymax = len+sd),width=0.2,position = position_dodge(0.05))+ geom_point(aes(color = supp))

以垂直线表示的间隔

f <- ggplot(df2, aes(x = dose, y = len,   ymin=len-sd, ymax=len+sd))f + geom_linerange()f + geom_pointrange()

点图与error bars 结合

g <- ggplot(df, aes(x=dose, y=len)) + geom_dotplot(binaxis='y', stackdir='center')# 用 geom_crossbar()g + stat_summary(fun.data="mean_sdl", fun.args = list(mult=1), geom="crossbar", width=0.5)# 用 geom_errorbar()g + stat_summary(fun.data=mean_sdl, fun.args = list(mult=1), geom="errorbar", color="red", width=0.2) + stat_summary(fun.y=mean, geom="point", color="red")# 用 geom_pointrange()g + stat_summary(fun.data=mean_sdl, fun.args = list(mult=1), geom="pointrange", color="red")

单基因泛癌分析

TCGA单基因免疫相关泛癌分析（应要求，对出图添加更细致的描述）

TCGA单基因免疫相关泛癌分析-进阶版本

资源贴

生信小课堂资源汇总