R语言可视化之UpSetR包

简介

集合可视化我们用得最多的是韦恩图，韦恩图在集合数少的时候是很好用的，但是当集合数多比如五个以上的时候那就会看花眼了，比如下面这副含有6个集合韦恩图，是发表在Nature上的文章里的，漂亮是漂亮，但是眼都快看花了。

今天介绍一个R包UpSetR，专门用来集合可视化，来源于 UpSet，Python里面也有一个相似的包py-upset。此外还有个 UpSetR shiny app以及 源代码.

安装

两种方式安装：

#从CRAN安装
install.packages("UpSetR")
#从Github上安装
devtools::install_github("hms-dbmi/UpSetR")

数据导入

UpSetR提供了两个函数fromList以及fromExpression将数据转换为UpsetR适用的数据格式。

#fromList
listinput <- list(one = c(1, 2, 3, 5, 7, 8, 11, 12, 13), two = c(1, 2, 4, 5, 
    10), three = c(1, 5, 6, 7, 8, 9, 10, 12, 13))
#fromExpression
expressionInput <- c(one = 2, two = 1, three = 2, `one&two` = 1, `one&three` = 4, 
    `two&three` = 1, `one&two&three` = 2)

接下来就可以绘制绘制图形了

library(UpSetR)
upset(fromList(listinput), order.by = "freq")
#下面绘制的图形等同于上图
upset(fromExpression(expressionInput), order.by = "freq")

参数详解

下面所有的例子都将使用UpSetR内置的数据集movies来绘制。

#导入数据
movies <- read.csv(system.file("extdata", "movies.csv", package = "UpSetR"), header = TRUE, sep = ";")
#先大致浏览一下该数据集,数据集太长，就只看前几列
knitr::kable(head(movies[,1:10]))

该数据集展示的是电影名（name）、发行时间（ReleaseDate）以及电影类型，多了去了就不详讲了，自个可以看去。 UpsetR绘制集合可视化图形使用函数upset()。

upset(movies, nsets = 6, number.angles = 30, point.size = 2, line.size = 1, mainbar.y.label = "Genre Intersections", sets.x.label = "Movies Per Genre", text.scale = c(1.3, 1.3, 1, 1, 1.5, 1))

解释一下上面部分参数：

• nsets: 顾名思义，就是展示几个集合，movies数据集由20几个集合，不可能全部展示，另外从图中可以看出，这6个集合应该不是按顺序选择的。
• numble.angle: 柱子上的数字看到了吧，这个参数就是调整数字角度的，可有可无的
• mainbar.y.label/sets.x.label：坐标轴名称
• text.scale(): 有六个数字，分别控制c(intersection size title, intersection size tick labels, set size title, set size tick labels, set names, numbers above bars)。

很多时候我们想要看特定的几个集合，UpSetR满足我们的需求。

upset(movies, sets = c("Action", "Adventure", "Comedy", "Drama", "Mystery", 
    "Thriller", "Romance", "War", "Western"), mb.ratio = c(0.55, 0.45), order.by = "freq")

文中的参数：

• mb.ratio: 控制上方条形图以及下方点图的比例
• order.by: 如何排序，这里freq表示从大到小排序展示，其他选项有degree以及先按freq再按degree排序。

各个变量也可以通过参数keep.order来排序

upset(movies, sets = c("Action", "Adventure", "Comedy", "Drama", "Mystery", 
    "Thriller", "Romance", "War", "Western"), mb.ratio = c(0.55, 0.45), order.by = "freq", 
    keep.order = TRUE)

也可以按group进行展示，这图展示的就是按各个变量自身、两个交集、三个交集…依次展示。参数cutoff控制每个group显示几个交集。 参数intersects控制总共显示几个交集。

upset(movies, nintersects = 70, group.by = "sets", cutoff = 7)

还有很多参数比如控制颜色的参数，点、线大小等，具体可查看?upset

queries参数

queries参数分为四个部分：query, param, color, active.

• query: 指定哪个query，UpSetR有内置的，也可以自定义，说到底就是一个查询函数
• param: list, query作用于哪个交集
• color：每个query都是一个list，里面可以设置颜色,没设置的话将调用包里默认的调色板
• active：被指定的条形图是否需要颜色覆盖，TRUE的话显示颜色，FALSE的话则在条形图顶端显示三角形

内置的intersects query

upset(movies, queries = list(list(query=intersects, params=list("Drama", "Comedy", "Action"), color="orange", active=T),
                             list(query=intersects, params=list("Drama"), color="red", active=F),
                             list(query=intersects, params=list("Action", "Drama"), active=T)))

内置的elements query

此query可以可视化特定交集在不同条件下的情况

upset(movies, queries = list(list(query=elements, params=list("AvgRating", 3.5, 4.1), color="blue", active=T),
                             list(query=elements, params=list("ReleaseDate", 1980, 1990, 2000), color="red", active=F)))

自定义一个query

myfunc <- function(row, release, rating){
  newdata <- (row["ReleaseDate"]%in%release)&(row["AvgRating"]>rating)
}
upset(movies, queries = list(list(query=myfunc, params=list(c(1950,1960,1990,2000), 3.0), color="red", active=T)))

添加query图例

upset(movies, query.legend = "top", queries = list(list(query = intersects, 
    params = list("Drama", "Comedy", "Action"), color = "orange", active = T, 
    query.name = "Funny action"), list(query = intersects, params = list("Drama"), 
    color = "red", active = F), list(query = intersects, params = list("Action", 
    "Drama"), active = T, query.name = "Emotional action")))

参数attribute.plots

主要是用于添加属性图，内置有柱形图、散点图、热图等

柱形图

upset(movies, main.bar.color = "black", queries = list(list(query = intersects, 
    params = list("Drama"), active = T)), attribute.plots = list(gridrows = 50, 
    plots = list(list(plot = histogram, x = "ReleaseDate", queries = F), list(plot = histogram, 
        x = "AvgRating", queries = T)), ncols = 2))

散点图

upset(movies, main.bar.color = "black", queries = list(list(query = intersects, 
    params = list("Drama"), color = "red", active = F), list(query = intersects, 
    params = list("Action", "Drama"), active = T), list(query = intersects, 
    params = list("Drama", "Comedy", "Action"), color = "orange", active = T)), 
    attribute.plots = list(gridrows = 45, plots = list(list(plot = scatter_plot, 
        x = "ReleaseDate", y = "AvgRating", queries = T), list(plot = scatter_plot, 
        x = "AvgRating", y = "Watches", queries = F)), ncols = 2), query.legend = "bottom")

箱线图

箱线图可以展示数据的分布,通过参数boxplot.summary控制，最多可以一次性显示两个箱线图

upset(movies, boxplot.summary = c("AvgRating", "ReleaseDate"))

还有一个十分重要的功能Incorporating Set Metadata这里就不讲了，有兴趣的可以参考这份 文档

SessionInfo

sessionInfo()
## R version 3.4.2 (2017-09-28)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 15063)
## 
## 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] UpSetR_1.3.3
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.13     knitr_1.17       magrittr_1.5     munsell_0.4.3   
##  [5] colorspace_1.3-2 rlang_0.1.2      stringr_1.2.0    highr_0.6       
##  [9] plyr_1.8.4       tools_3.4.2      grid_3.4.2       gtable_0.2.0    
## [13] htmltools_0.3.6  yaml_2.1.14      lazyeval_0.2.0   rprojroot_1.2   
## [17] digest_0.6.12    tibble_1.3.4     gridExtra_2.3    ggplot2_2.2.1   
## [21] evaluate_0.10.1  rmarkdown_1.6    labeling_0.3     stringi_1.1.5   
## [25] compiler_3.4.2   scales_0.5.0     backports_1.1.1