解析维恩表以在 R 中创建维恩图答案

【问题标题】：Parsing venn table to create Venn Diagram in R解析维恩表以在 R 中创建维恩图
【发布时间】：2016-05-04 18:02:29
【问题描述】：

我有带有维恩图值的表格，我试图将其读入 R 并解析，以便使用 VennDiagram 包进行绘图。我的表格如下所示：

H3K27AC.bed H3K4ME3.bed gencode.bed Total   Name
        X   19184   gencode.bed
    X       6843    H3K4ME3.bed
    X   X   3942    H3K4ME3.bed|gencode.bed
X           5097    H3K27AC.bed
X       X   1262    H3K27AC.bed|gencode.bed
X   X       4208    H3K27AC.bed|H3K4ME3.bed
X   X   X   9222    H3K27AC.bed|H3K4ME3.bed|gencode.bed

我可以像这样以数据框的形式读取表格：

> venn_table_df<-read.table(venn_table_file,header = TRUE,sep = "\t",stringsAsFactors = FALSE)
> venn_table_df
  H3K27AC.bed H3K4ME3.bed gencode.bed Total                                Name
1                                   X 19184                         gencode.bed
2                       X              6843                         H3K4ME3.bed
3                       X           X  3942             H3K4ME3.bed|gencode.bed
4           X                          5097                         H3K27AC.bed
5           X                       X  1262             H3K27AC.bed|gencode.bed
6           X           X              4208             H3K27AC.bed|H3K4ME3.bed
7           X           X           X  9222 H3K27AC.bed|H3K4ME3.bed|gencode.bed

我可以像这样从表格中获取维恩图的类别

> venn_categories<-colnames(venn_table_df)[!colnames(venn_table_df) %in% c("Total","Name")] 
> venn_categories
[1] "H3K27AC.bed" "H3K4ME3.bed" "gencode.bed"

我什至可以制作一个更易于阅读的汇总表，如下所示：

> venn_summary<-venn_table_df[!colnames(venn_table_df) %in% venn_categories]
> venn_summary
  Total                                Name
1 19184                         gencode.bed
2  6843                         H3K4ME3.bed
3  3942             H3K4ME3.bed|gencode.bed
4  5097                         H3K27AC.bed
5  1262             H3K27AC.bed|gencode.bed
6  4208             H3K27AC.bed|H3K4ME3.bed
7  9222 H3K27AC.bed|H3K4ME3.bed|gencode.bed

但困扰我的是如何从表格中取出值并将它们正确分配给维恩图的区域。作为参考，三重维恩函数如下所示：

n1<-5097
n2<-6843
n3<-19184

n12<-4208
n13<-1262
n23<-3942

n123<-9222

venn <-draw.triple.venn(area1=n1+n12+n13+n123,
                        area2=n2+n23+n12+n123,
                        area3=n3+n23+n13+n123,
                        n12=n12+n123,
                        n13=n13+n123,
                        n23=n23+n123,
                        n123=n123,
                        category=venn_categories,
                        fill=c('red','blue','green'),
                        alpha=c(rep(0.3,3)))

但显然这需要手动设置值，这是不可取的，因为我有很多这样的数据集，并且还需要将其扩展到 4 路和 5 路维恩。如何让 R 找到维恩中每个字段的正确值？我尝试了多种不同的方法，使用grep、grepl，并为与绘图的每个区域的类别匹配的行设置数据框子集，但这并没有正常工作。有什么建议么？顺便说一句，此数据是从 HOMER 软件包的 mergePeaks 程序输出的。

【问题讨论】：

您的问题是关于如何计算 n1、n2 等数字吗？扩展到 4 或 5 组是一个不同的问题。你能澄清一下吗？
数字已经计算好了。问题是将表格中的数字放到图中的正确位置。但我想我想通了，不得不使用正则表达式搜索，给我一分钟，我会发布它。

标签： r venn-diagram

【解决方案1】：

我想我想通了，使用正则表达式在表格中搜索正确的情节条目。这是完整的工作流程：

# load packages
library('VennDiagram')
library('gridExtra')

# read in the venn text
venn_table_df<-read.table(venn_table_file,header = TRUE,sep = "\t",stringsAsFactors = FALSE)
venn_table_df

看起来像这样：

> venn_table_df
  H3K27AC.bed H3K4ME3.bed gencode.bed Total                                Name
1                                   X 19184                         gencode.bed
2                       X              6843                         H3K4ME3.bed
3                       X           X  3942             H3K4ME3.bed|gencode.bed
4           X                          5097                         H3K27AC.bed
5           X                       X  1262             H3K27AC.bed|gencode.bed
6           X           X              4208             H3K27AC.bed|H3K4ME3.bed
7           X           X           X  9222 H3K27AC.bed|H3K4ME3.bed|gencode.bed

> # recreate it with this btw
> dput(venn_table_df)
structure(list(H3K27AC.bed = c("", "", "", "X", "X", "X", "X"
), H3K4ME3.bed = c("", "X", "X", "", "", "X", "X"), gencode.bed = c("X", 
"", "X", "", "X", "", "X"), Total = c(19184L, 6843L, 3942L, 5097L, 
1262L, 4208L, 9222L), Name = c("gencode.bed", "H3K4ME3.bed", 
"H3K4ME3.bed|gencode.bed", "H3K27AC.bed", "H3K27AC.bed|gencode.bed", 
"H3K27AC.bed|H3K4ME3.bed", "H3K27AC.bed|H3K4ME3.bed|gencode.bed"
)), .Names = c("H3K27AC.bed", "H3K4ME3.bed", "gencode.bed", "Total", 
"Name"), class = "data.frame", row.names = c(NA, -7L))

然后解析表格

# get the venn categories
venn_categories<-colnames(venn_table_df)[!colnames(venn_table_df) %in% c("Total","Name")] 


# make a summary table
venn_summary<-venn_table_df[!colnames(venn_table_df) %in% venn_categories]
venn_summary

# get the areas for the venn; add up all the overlaps that contain the given category 

# area1
area_n1<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[1],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])

# area2
area_n2<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[2],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])

# area3
area_n3<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[3],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])

# n12
area_n12<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[1],")","(?=.*",venn_categories[2],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])

# n13
area_n13<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[1],")","(?=.*",venn_categories[3],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])

# n23
area_n23<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[2],")","(?=.*",venn_categories[3],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])


# n123
area_n123<-sum(venn_summary[grep(pattern = paste0("(?=.*",venn_categories[1],")","(?=.*",venn_categories[2],")","(?=.*",venn_categories[3],")"),x = venn_summary$Name,perl = TRUE),][["Total"]])


venn <-draw.triple.venn(area1=area_n1,
                        area2=area_n2,
                        area3=area_n3,
                        n12=area_n12,
                        n13=area_n13,
                        n23=area_n23,
                        n123=area_n123,
                        category=venn_categories,
                        fill=c('red','blue','green'),
                        alpha=c(rep(0.3,3)))

关键是使用正则表达式仅获取包含 venn 区域的所有类别的表条目。这比我希望的要复杂一些，并且需要手动设置以适应四路和五路 venns，但到目前为止它仍然有效。我愿意接受其他可能能够简化流程并更容易扩大规模的建议。

【讨论】：

【解决方案2】：

如果有人觉得这很有用，现在有一个非常简单的程序可以将这些数字转换为近似成比例的维恩图。使用 nVennR 包创建图表的方法之一是从头开始。正如vignette 中所解释的，每个区域的值都按特定顺序输入，这恰好与您的表格中的相同。唯一的区别是 nVennR 在开始时期望多一个值，对应于外部区域（这个值应该是 0，但无论如何都会被忽略）。这使得该过程非常简单：

> vt <- read.table('clipboard', header = T)
> vt
  H3K27AC.bed H3K4ME3.bed gencode.bed Total                                Name
1           0           0           X 19184                         gencode.bed
2           0           X           0  6843                         H3K4ME3.bed
3           0           X           X  3942             H3K4ME3.bed|gencode.bed
4           X           0           0  5097                         H3K27AC.bed
5           X           0           X  1262             H3K27AC.bed|gencode.bed
6           X           X           0  4208             H3K27AC.bed|H3K4ME3.bed
7           X           X           X  9222 H3K27AC.bed|H3K4ME3.bed|gencode.bed
> myV <- createVennObj(nSets = 3, sNames = c('H3K27Ac', 'H3K4ME3', 'gencode'), sSizes = c(0, vt$Total))
> vp <- plotVenn(nVennObj = myV)

结果：此过程的另一个优点是它可以扩展到更多的组。

【讨论】：