r - 如何在R中制作维恩图？

Question

嗨，我是 R 新手，我必须使用它来制作维恩图。我已经在谷歌上搜索了一段时间，我能找到的所有示例都涉及二进制变量。不过我有 2 个列表(实际上是 2 个 csv 文件)。列表中的项目只是字符串，例如 PSF113_xxxx。我必须对它们进行比较，看看它们各自的独特之处和共同点。我如何在 R 中制作维恩图？

此外，这些文件中的内容数量也不相同，其中一个文件的内容数量略多于另一个文件，这意味着 cbind 函数会返回错误。

到目前为止我已经想出了这个，但这只是给我一个图像，其中有一个名为组 1 的圆圈，里面有 1，外面有 0。

matLis <- list(matrix(A), matrix(B))

n <- max(sapply(matLis, nrow))
do.call(cbind, lapply(matLis, function (x)
     rbind(x, matrix(, n-nrow(x), ncol(x))))) 

x = vennCounts(n)
vennDiagram(x)

这是数据示例

2 PSF113_0018
3 PSF113_0079
4 PSF113_0079a
5 PSF113_0079b

左侧的编号不是我所做的任何事情，它是当我将文件从 excel 导入到 R 时添加的

head(A)
> head(A)
            V1
1 PSF113_0016a
2  PSF113_0018
3  PSF113_0079
4 PSF113_0079a
5 PSF113_0079b
6 PSF113_0079c

> head(b,10)
             V1
1  PSF113_0016a
2   PSF113_0021
3   PSF113_0048
4   PSF113_0079
5  PSF113_0079a
6  PSF113_0079b
7  PSF113_0079c
8   PSF113_0295
9  PSF113_0324a
10 PSF113_0324b

Answer 1

您的代码仍然不太可重现，因为您还没有定义 A 或 B。这是 venneuler 包中的维恩图指南，因为我发现它更灵活。

List1 <- c("apple", "apple", "orange", "kiwi", "cherry", "peach")
List2 <- c("apple", "orange", "cherry", "tomatoe", "pear", "plum", "plum")
Lists <- list(List1, List2)  #put the word vectors into a list to supply lapply
items <- sort(unique(unlist(Lists)))   #put in alphabetical order
MAT <- matrix(rep(0, length(items)*length(Lists)), ncol=2)  #make a matrix of 0's
colnames(MAT) <- paste0("List", 1:2)
rownames(MAT) <- items
lapply(seq_along(Lists), function(i) {   #fill the matrix
    MAT[items %in% Lists[[i]], i] <<- table(Lists[[i]])
})

MAT   #look at the results
library(venneuler)
v <- venneuler(MAT)
plot(v)

编辑: 头部非常有帮助，因为它为我们提供了一些可以使用的东西。尝试这种方法:

#For reproducibility (skip this and read in the csv files)
A <- structure(list(V1 = structure(1:6, .Label = c("PSF113_0016a", 
    "PSF113_0018", "PSF113_0079", "PSF113_0079a", "PSF113_0079b", 
    "PSF113_0079c"), class = "factor")), .Names = "V1", 
    class = "data.frame", row.names = c("1", 
    "2", "3", "4", "5", "6"))

B <- structure(list(V1 = structure(1:10, .Label = c("PSF113_0016a", 
    "PSF113_0021", "PSF113_0048", "PSF113_0079", "PSF113_0079a", 
    "PSF113_0079b", "PSF113_0079c", "PSF113_0295", "PSF113_0324a", 
    "PSF113_0324b"), class = "factor")), .Names = "V1", 
    class = "data.frame", row.names = c("1", 
    "2", "3", "4", "5", "6", "7", "8", "9", "10"))

从这里运行代码:

#after reading in the csv files start here
Lists <- list(A, B)  #put the word vectors into a list to supply lapply
Lists <- lapply(Lists, function(x) as.character(unlist(x)))
items <- sort(unique(unlist(Lists)))   #put in alphabetical order
MAT <- matrix(rep(0, length(items)*length(Lists)), ncol=2)  #make a matrix of 0's
colnames(MAT) <- paste0("List", 1:2)
rownames(MAT) <- items
lapply(seq_along(Lists), function(i) {   #fill the matrix
    MAT[items %in% Lists[[i]], i] <<- table(Lists[[i]])
})

MAT   #look at the results
library(venneuler)
v <- venneuler(MAT)
plot(v)

这种方法的不同之处在于，我取消列出了两个数据帧(如果它们是数据帧)，然后将它们转换为字符向量。我认为这应该可行。