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ggpubr:快速绘制用于发表的图形

ggplot2 (Hadley Wickham开发)是目前R语言数据可视化的主流。与R的基础绘图系统相比,基于grid绘图系统的ggplot2已经在语法理解性上已经进步很多,但是通过ggplot2绘制用于学术杂志的图形,仍然需要较多的绘图函数(或者加载一些写好的模板代码)。为此Alboukadel Kassambara基于ggplot2、ggsci包开发了ggpubr用于绘制符合出版物要求的图形。该包封装了很多ggplot2的绘图函数,并且内嵌了ggsci中很多优秀的学术期刊配色方案,值得学习使用。ggpubr包括一些关键的特性:

  • 能帮助研究人员快速创建易于发表的图形;
  • 能够将P值和显著性水平自动添加到图形上而无需二次编辑;
  • 使图形注释和排版变得容易;
  • 使更改图形参数(例如颜色和标签)变得容易。

安装

从CRAN安装:

install.packages("ggpubr")

或者也可以从Github安装最新版本:

if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")

加载ggpubr包:

library("ggpubr")

ggpubr可绘制的图形

加载数据

library(ggpubr)

set.seed(1234)
wdata = data.frame(
   sex = factor(rep(c("F", "M"), each=200)),
   weight = c(rnorm(200, 55), rnorm(200, 58)))
head(wdata, 4)

##   sex weight
## 1   F   53.8
## 2   F   55.3
## 3   F   56.1
## 4   F   52.7

密度图

# 带有平均值线和边际地毯的密度图
ggdensity(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))
ggpubr:快速绘制用于发表的图形

直方图

# 带有平均值线和边际地毯的直方图
gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))
ggpubr:快速绘制用于发表的图形

箱线图和小提琴图

# 加载数据
data("ToothGrowth")
df <- ToothGrowth
head(df, 4)
##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
# 带有抖动点图的箱线图
p <- ggboxplot(df, x = "dose", y = "len",
                color = "dose", palette =c("#00AFBB", "#E7B800", "#FC4E07"),
                add = "jitter", shape = "dose")
p
ggpubr:快速绘制用于发表的图形
# 添加P值
my_comparisons <- list( c("0.5", "1"), c("1", "2"), c("0.5", "2") )
p + stat_compare_means(comparisons = my_comparisons)+ # 添加每两组间的P值
  stat_compare_means(label.y = 50) # 添加全局P值
ggpubr:快速绘制用于发表的图形
# 带有箱线图的小提琴图
ggviolin(df, x = "dose", y = "len", fill = "dose",
         palette = c("#00AFBB", "#E7B800", "#FC4E07"),
         add = "boxplot", add.params = list(fill = "white"))+
  stat_compare_means(comparisons = my_comparisons, label = "p.signif")+ # 添加显著性水平
  stat_compare_means(label.y = 50) # 添加全局P值
ggpubr:快速绘制用于发表的图形

条形图

数据加载

data("mtcars")
dfm <- mtcars
dfm$cyl <- as.factor(dfm$cyl)
dfm$name <- rownames(dfm)
head(dfm[, c("name", "wt", "mpg", "cyl")])

##                                name   wt  mpg cyl
## Mazda RX4                 Mazda RX4 2.62 21.0   6
## Mazda RX4 Wag         Mazda RX4 Wag 2.88 21.0   6
## Datsun 710               Datsun 710 2.32 22.8   4
## Hornet 4 Drive       Hornet 4 Drive 3.21 21.4   6
## Hornet Sportabout Hornet Sportabout 3.44 18.7   8
## Valiant                     Valiant 3.46 18.1   6

有序条形图

通过cyl更改填充色,并且对全部数据进行排序, 而非分组排序。

ggbarplot(dfm, x = "name", y = "mpg",
          fill = "cyl",               
          color = "white",            
          palette = "jco",            
          sort.val = "desc",          
          sort.by.groups = FALSE,     
          x.text.angle = 90           
          )
ggpubr:快速绘制用于发表的图形

对每组内的数据进行排序,可设置sort.by.groups = TRUE。

ggbarplot(dfm, x = "name", y = "mpg",
          fill = "cyl",               
          color = "white",            
          palette = "jco",            
          sort.val = "asc",           
          sort.by.groups = TRUE,      
          x.text.angle = 90           
          )
ggpubr:快速绘制用于发表的图形

偏差图

偏差图一般用以展示变量与参考值之间的偏差程度。下面将以mtcars数据集中的mpg z-score来绘制偏差图。
计算mpg数据的z-score:

dfm$mpg_z <- (dfm$mpg -mean(dfm$mpg))/sd(dfm$mpg)
dfm$mpg_grp <- factor(ifelse(dfm$mpg_z < 0, "low", "high"), 
                     levels = c("low", "high"))

head(dfm[, c("name", "wt", "mpg", "mpg_z", "mpg_grp", "cyl")])
##                                name   wt  mpg  mpg_z mpg_grp cyl
## Mazda RX4                 Mazda RX4 2.62 21.0  0.151    high   6
## Mazda RX4 Wag         Mazda RX4 Wag 2.88 21.0  0.151    high   6
## Datsun 710               Datsun 710 2.32 22.8  0.450    high   4
## Hornet 4 Drive       Hornet 4 Drive 3.21 21.4  0.217    high   6
## Hornet Sportabout Hornet Sportabout 3.44 18.7 -0.231     low   8
## Valiant                     Valiant 3.46 18.1 -0.330     low   6

绘制分组排序的条形图:

ggbarplot(dfm, x = "name", y = "mpg_z",
          fill = "mpg_grp",           
          color = "white",            
          palette = "jco",            
          sort.val = "asc",           
          sort.by.groups = FALSE,     
          x.text.angle = 90,          
          ylab = "MPG z-score",
          xlab = FALSE,
          legend.title = "MPG Group"
          )
ggpubr:快速绘制用于发表的图形

旋转图形:

ggbarplot(dfm, x = "name", y = "mpg_z",
          fill = "mpg_grp",           
          color = "white",            
          palette = "jco",            
          sort.val = "desc",          
          sort.by.groups = FALSE,     
          x.text.angle = 90,          
          ylab = "MPG z-score",
          legend.title = "MPG Group",
          rotate = TRUE,
          ggtheme = theme_minimal()
          )
ggpubr:快速绘制用于发表的图形

点图

棒棒糖图

当你有大量数据来展示时,棒棒糖图与上面所说的条形图的效果是类似的。

棒棒糖图的颜色可以根据分组变量“cyl”确定:

ggdotchart(dfm, x = "name", y = "mpg",
           color = "cyl",                                
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), 
           sorting = "ascending",                        
           add = "segments",                             
           ggtheme = theme_pubr()                        
           )
ggpubr:快速绘制用于发表的图形

旋转并更改点大小:

ggdotchart(dfm, x = "name", y = "mpg",
           color = "cyl",                                
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), 
           sorting = "descending",                       
           add = "segments",                             
           rotate = TRUE,                                
           group = "cyl",                                
           dot.size = 6,                                 
           label = round(dfm$mpg),                       
           font.label = list(color = "white", size = 9, 
                             vjust = 0.5),              
           ggtheme = theme_pubr()                        
           )
ggpubr:快速绘制用于发表的图形

偏差图

ggdotchart(dfm, x = "name", y = "mpg_z",
           color = "cyl",                                
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), 
           sorting = "descending",                       
           add = "segments",                             
           add.params = list(color = "lightgray", size = 2), 
           group = "cyl",                                
           dot.size = 6,                                 
           label = round(dfm$mpg_z,1),                        
           font.label = list(color = "white", size = 9, 
                             vjust = 0.5),               
           ggtheme = theme_pubr()                        
           )+
  geom_hline(yintercept = 0, linetype = 2, color = "lightgray")
ggpubr:快速绘制用于发表的图形

Cleveland点图

ggdotchart(dfm, x = "name", y = "mpg",
           color = "cyl",                                
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), 
           sorting = "descending",                       
           rotate = TRUE,                                
           dot.size = 2,                                 
           y.text.col = TRUE,                            
           ggtheme = theme_pubr()                        
           )+
  theme_cleveland()   
ggpubr:快速绘制用于发表的图形

运行环境

sessionInfo()
R version 3.6.2 (2019-12-12)
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_0.2.4  magrittr_1.5  ggplot2_3.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3       rstudioapi_0.10  tidyselect_0.2.5 munsell_0.5.0   
 [5] colorspace_1.4-1 R6_2.4.1         rlang_0.4.3      dplyr_0.8.3     
 [9] tools_3.6.2      grid_3.6.2       gtable_0.3.0     withr_2.1.2     
[13] lazyeval_0.2.2   assertthat_0.2.1 digest_0.6.23    tibble_2.1.3    
[17] lifecycle_0.1.0  ggsignif_0.6.0   crayon_1.3.4     ggsci_2.9       
[21] purrr_0.3.3      farver_2.0.3     glue_1.3.1       labeling_0.3    
[25] compiler_3.6.2   pillar_1.4.3     scales_1.1.0     pkgconfig_2.0.3 

参考

本文由 Chipcui 创作

本文来自https://blog.chipcui.top,观点不代表一起大数据立场,如若转载,请注明出处:https://blog.chipcui.top/archives/ggpubr-publication-ready-plots

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