03.条形图绘制
清除当前环境中的变量
rm(list=ls())
设置工作目录
setwd("C:/Users/Dell/Desktop/R_Plots/03barplot/")
barplot函数绘制条形图
# 使用mtcars内置数据集
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
# 使用table函数进行计数
counts <- table(mtcars$cyl)
counts
##
## 4 6 8
## 11 7 14
# 默认条形图垂直放置
barplot(counts,xlab = "mtcars$cyl", ylab = "counts",
col = heat.colors(3))
image.png
# 设置horiz = T参数进行水平放置
barplot(counts,xlab = "mtcars$cyl", ylab = "counts",
col = heat.colors(3), horiz = T)
image.png
# 绘制分组条形图
counts <- table(mtcars$cyl,mtcars$carb)
counts
##
## 1 2 3 4 6 8
## 4 5 6 0 0 0 0
## 6 2 0 0 4 1 0
## 8 0 4 3 6 0 1
# 默认为堆砌条形图
barplot(counts, xlab = "cyl", ylab = "carb", legend = T,
col = c("red","blue","green"), main = "Group of cyl and carb")
image.png
# 设置beside = T参数绘制并列分组条形图
barplot(counts, xlab = "cyl", ylab = "carb", beside = T, legend = T,
col = c("red","blue","green"), main = "Group of cyl and carb")
image.png
ggplot2包绘制分组条形图
# 读取示例数据
data <- read.table("demo1_barplot.txt",header = T, check.names = F, sep = "\t")
# 查看数据
head(data)
## Annotation cluster_1 cluster_2 cluster_3
## 1 Naive B cells 8 96 875
## 2 Mature B cells class switched 7 51 337
## 3 Mature B cells class able to switch 2 22 280
## 4 Mature B cells 1 12 131
## 5 Pro B cells 457 196 1044
## 6 Early B cells 33 204 106
## cluster_4 cluster_5
## 1 2071 2392
## 2 1187 1590
## 3 856 1079
## 4 294 353
## 5 689 256
## 6 108 37
library(ggplot2)
library(reshape2)
data <- melt(data,variable.name = "Cluster", value.name = "Count")
## Using Annotation as id variables
head(data)
## Annotation Cluster Count
## 1 Naive B cells cluster_1 8
## 2 Mature B cells class switched cluster_1 7
## 3 Mature B cells class able to switch cluster_1 2
## 4 Mature B cells cluster_1 1
## 5 Pro B cells cluster_1 457
## 6 Early B cells cluster_1 33
# 设置position = "stack"参数绘制堆砌条形图
ggplot(data, aes(Cluster, Count, fill=Annotation)) +
geom_bar(stat = "identity", position = "stack") + theme_bw() + theme(legend.position = "top")
image.png
# 设置position = "dodge"参数绘制并列条形图
ggplot(data, aes(Cluster, Count, fill=Annotation)) +
geom_bar(stat = "identity", position = "dodge") + theme_bw() + theme(legend.position = "top")
image.png
# 设置position = "fill"参数绘制填充条形图
ggplot(data, aes(Cluster, Count, fill=Annotation)) +
geom_bar(stat = "identity", position = "fill") + theme_bw() + theme(legend.position = "top")
image.png
# 添加coord_flip参数进行水平翻转
ggplot(data, aes(Cluster, Count, fill=Annotation)) +
geom_bar(stat = "identity", position = "fill") +
theme_bw() + theme(legend.position = "top") + coord_flip()
image.png
ggpubr包绘制带误差棒的条形图
# 读取示例数据
data <- read.table("demo2_barplot.txt",header = T,row.names = 1, check.names = F, sep = "\t")
# 查看数据
head(data)
## Gender Stage GeneSymbol TPM
## GSM1328533 Female 2 weeks Egfr 1.296193
## GSM1328534 Female 2 weeks Egfr 1.337968
## GSM1328535 Female 2 weeks Egfr 1.352709
## GSM1328536 Female 2 weeks Egfr 1.293170
## GSM1328537 Female 6 weeks Egfr 1.059719
## GSM1328538 Female 6 weeks Egfr 1.184652
library(ggpubr)
ggbarplot(data, x = "Stage", y = "TPM",
color = "Gender", fill = "Gender",
add = c("mean_se","dotplot"), width = 0.6,
position = position_dodge())
image.png
ggbarplot(data, x = "Stage", y = "TPM", orientation = "horiz",
color = "Gender", fill = "Gender",
add = c("mean_se","jitter"), width = 0.6,
palette = c("#00AFBB", "#E7B800"),
position = position_dodge())
image.png
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936
## [2] LC_CTYPE=Chinese (Simplified)_China.936
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggpubr_0.2.1 magrittr_1.5 reshape2_1.4.3 ggplot2_3.2.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.1 knitr_1.23 tidyselect_0.2.5 munsell_0.5.0
## [5] colorspace_1.4-1 R6_2.4.0 rlang_0.4.0 plyr_1.8.4
## [9] stringr_1.4.0 dplyr_0.8.3 tools_3.6.0 grid_3.6.0
## [13] gtable_0.3.0 xfun_0.8 withr_2.1.2 htmltools_0.3.6
## [17] yaml_2.2.0 lazyeval_0.2.2 digest_0.6.20 assertthat_0.2.1
## [21] tibble_2.1.3 ggsignif_0.5.0 crayon_1.3.4 purrr_0.3.2
## [25] glue_1.3.1 evaluate_0.14 rmarkdown_1.13 labeling_0.3
## [29] stringi_1.4.3 compiler_3.6.0 pillar_1.4.2 scales_1.0.0
## [33] pkgconfig_2.0.2
