解析维恩表以在R中创建维恩图

Question

我有一些带有维恩图值的表，我试图将这些值读入R并进行解析，以便使用VennDiagram软件包进行绘制。 我的表如下所示：

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

我可以像这样在数据框中读取表：

> 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

我可以从这样的表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摘要表，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

但是让我感到困扰的是如何从表中获取值并将它们正确地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)))

但这显然需要手动设置值，这是不理想的，因为我拥有许多这些数据集，并且还需要将其扩展到4路和5路Venn。 如何获得R为维恩中的每个字段找到正确的值？ 我已经尝试使用grep ， grepl和将子帧的数据grepl为与图的每个区域相匹配的行的多种方法，但是这种方法无法正常工作。 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。

Answer 1

我想我已经解决了，使用正则表达式在表格中搜索情节的正确条目。 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

# 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维恩区域所有类别的表条目。 这比我期望的要复杂得多，并且需要手动设置以适应四向和五向静脉，但是到目前为止，它仍然有效。 我对其他建议持开放态度，这些建议可能能够简化流程并更容易地扩大规模。

Answer 2

万一有人觉得这有用，现在有一个非常简单的过程可以将这些数字转换成近似成比例的维恩图。 使用nVennR软件包创建图表的方法之一是从头开始。 如小插图中所述，每个区域的值以特定顺序输入，恰好与表中的相同。 唯一的区别是nVennR期望在开始时再加上一个值，该值对应于外部区域（该值应为0，但无论如何它将被忽略）。 这使过程非常容易：

> 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。