R尽管数字正确，但“ draw.quad.venn中的错误，不可能：产生负区域”

Question

我正在尝试使用R中的VennDiagram包中的draw.quad.venn生成四向维恩图，但它会不断抛出错误消息：

ERROR [2019-05-14 11:28:24] Impossible: a7  <- n234 - a6 produces negative area
Error in draw.quad.venn(length(gene_lists[[1]]), length(gene_lists[[2]]),  : 
  Impossible: a7  <- n234 - a6 produces negative area

我正在使用4个不同的基因列表作为输入。 calculate.overlap效果很好，然后我通过使用length（x）函数对重叠值（解析为列表）获取数字。我将所有重叠值以及适当的总组大小传递给draw.quad.venn函数，但它一直声称其中一个组是不可能的，因为它会生成负数。

我已经手动检查了数字，它们显然加起来为正确的值。我还对20000个基因的随机集合进行了测试，该基因使用类似于下面的脚本生成，并且可以正常工作，即生成四向维恩图。除了它们的大小，随机生成的基因列表与我从实际结果文件中挑选的基因列表之间没有区别。下面是一个最小的工作示例：

# working example that fails
# get vector of 10000 elements (representative of gene list)
values <- c(1:10000)
# generate 4 subsets by random sampling
list_1 <- sample(values, size = 5000, replace = FALSE)
list_2 <- sample(values, size = 4000, replace = FALSE)
list_3 <- sample(values, size = 3000, replace = FALSE)
list_4 <- sample(values, size = 2000, replace = FALSE)
# compile them in to a list
lists <- list(list_1, list_2, list_3, list_4)
# find overlap between all possible combinations (11 plus 4 unique to each list = 15 total)
overlap <- calculate.overlap(lists)
# get the lengths of each list - these will be the numbers used for the Venn diagram
overlap_values <- lapply(overlap, function(x) length(x))
# rename overlap values (easier to identify which groups are intersecting)
names(overlap_values) <- c("n1234", "n123", "n124", "n134", "n234", "n12", "n13", "n14", "n23", "n24", "n34", "n1", "n2", "n3", "n4")
# generate the venn diagram
draw.quad.venn(length(lists[[1]]), length(lists[[2]]), length(lists[[3]]), length(lists[[4]]), overlap_values$n12,
               overlap_values$n13, overlap_values$n14, overlap_values$n23, overlap_values$n24, overlap_values$n34,
               overlap_values$n123, overlap_values$n124, overlap_values$n134, overlap_values$n234, overlap_values$n1234)

我希望有四个方向的维恩图，无论某些组是否为0，它们仍然应该存在，但标记为0。这应该是这样的：

我不确定是否是因为我在真实数据中有0个值，即某些没有重叠的组？有什么办法可以强制draw.quad.venn（）取任何值？如果没有，我是否可以使用另一个软件包来获得相同的结果？任何帮助，不胜感激！

Answer 1

因此，我尝试使用VennDiagram包中的draw.quad.venn不能解决任何错误。编写方式有问题。只要4个椭圆中每个椭圆的所有数字加起来都等于该特定列表中元素的总数，维恩图就有效。由于某种原因，VennDiagram仅接受较少的交点导致较高的数字（例如组1、2和3的交集必须高于所有4组的交集。这并不代表现实世界的数据。第1、2和3组完全不相交，而所有4个组都相交。在维恩图中，所有数字都是独立的，并且表示每个交叉点共有的元素总数。他们不必互相影响。

我看了eulerr软件包，但实际上找到了一种非常简单的方法，在gplots中使用venn绘制venn图，如下所示：

# simple 4 way Venn diagram using gplots
# get some mock data
values <- c(1:20000)
list_1 <- sample(values, size = 5000, replace = FALSE)
list_2 <- sample(values, size = 4000, replace = FALSE)
list_3 <- sample(values, size = 3000, replace = FALSE)
list_4 <- sample(values, size = 2000, replace = FALSE)
lists <- list(list_1, list_2, list_3, list_4)
# name thec list (required for gplots)
names(lists) <- c("G1", "G2", "G3", "G4")
# get the venn table
v.table <- venn(lists)
# show venn table
print(v.table)
# plot Venn diagram
plot(v.table)

我现在考虑解决问题。谢谢zx8754的帮助！

Answer 2

我看过了软件包的源代码。如果您仍然对错误的原因感兴趣，可以使用两种方法将数据发送到venn.diagram。一种是nxxxx（例如n134）形式，另一种是an（例如a5）形式。在示例中，n134的意思是“哪些元素至少属于组1、3和4”。另一方面，a5表示“哪些元素仅属于组1、3和4”。两种形式之间的关系确实很复杂，例如a6对应于n1234。这意味着n134 = a5 + a6。 问题是calculate.overlap以an的形式给出数字，而默认情况下draw.quad.venn期望以nxxxx的形式给出数字。要使用calculate.overlap中的值，可以将direct.area设置为true，并在calculate.overlap参数中提供area.vector的结果。例如，

tmp <- calculate.overlap(list(a=c(1, 2, 3, 4, 10), b=c(3, 4, 5, 6), c=c(4, 6, 7, 8, 9), d=c(4, 8, 1, 9)))
overlap_values <- lapply(tmp, function(x) length(x))
draw.quad.venn(area.vector = c(overlap_values$a1, overlap_values$a2, overlap_values$a3, overlap_values$a4, 
                               overlap_values$a5, overlap_values$a6, overlap_values$a7, overlap_values$a8, 
                               overlap_values$a9, overlap_values$a10, overlap_values$a11, overlap_values$a12, 
                               overlap_values$a13, overlap_values$a14, overlap_values$a15), direct.area = T, category = c('a', 'b', 'c', 'd'))

如果您对更简单，更灵活的东西感兴趣，我为此类问题制作了nVennR软件包：

library(nVennR)
g1 <- c('AF029684', 'M28825', 'M32074', 'NM_000139', 'NM_000173', 'NM_000208', 'NM_000316', 'NM_000318', 'NM_000450', 'NM_000539', 'NM_000587', 'NM_000593', 'NM_000638', 'NM_000655', 'NM_000789', 'NM_000873', 'NM_000955', 'NM_000956', 'NM_000958', 'NM_000959', 'NM_001060', 'NM_001078', 'NM_001495', 'NM_001627', 'NM_001710', 'NM_001716')
g2 <- c('NM_001728', 'NM_001835', 'NM_001877', 'NM_001954', 'NM_001992', 'NM_002001', 'NM_002160', 'NM_002162', 'NM_002258', 'NM_002262', 'NM_002303', 'NM_002332', 'NM_002346', 'NM_002347', 'NM_002349', 'NM_002432', 'NM_002644', 'NM_002659', 'NM_002997', 'NM_003032', 'NM_003246', 'NM_003247', 'NM_003248', 'NM_003259', 'NM_003332', 'NM_003383', 'NM_003734', 'NM_003830', 'NM_003890', 'NM_004106', 'AF029684', 'M28825', 'M32074', 'NM_000139', 'NM_000173', 'NM_000208', 'NM_000316', 'NM_000318', 'NM_000450', 'NM_000539')
g3 <- c('NM_000655', 'NM_000789', 'NM_004107', 'NM_004119', 'NM_004332', 'NM_004334', 'NM_004335', 'NM_004441', 'NM_004444', 'NM_004488', 'NM_004828', 'NM_005214', 'NM_005242', 'NM_005475', 'NM_005561', 'NM_005565', 'AF029684', 'M28825', 'M32074', 'NM_005567', 'NM_003734', 'NM_003830', 'NM_003890', 'NM_004106', 'AF029684', 'NM_005582', 'NM_005711', 'NM_005816', 'NM_005849', 'NM_005959', 'NM_006138', 'NM_006288', 'NM_006378', 'NM_006500', 'NM_006770', 'NM_012070', 'NM_012329', 'NM_013269', 'NM_016155', 'NM_018965', 'NM_021950', 'S69200', 'U01351', 'U08839', 'U59302')
g4 <- c('NM_001728', 'NM_001835', 'NM_001877', 'NM_001954', 'NM_005214', 'NM_005242', 'NM_005475', 'NM_005561', 'NM_005565', 'ex1', 'ex2', 'NM_003890', 'NM_004106', 'AF029684', 'M28825', 'M32074', 'NM_000139', 'NM_000173', 'NM_000208', 'NM_000316', 'NM_000318', 'NM_000450', 'NM_000539')
myV <- plotVenn(list(g1=g1, g2=g2, g3=g3, g4=g4))
myV <- plotVenn(nVennObj = myV)
myV <- plotVenn(nVennObj = myV)

故意重复最后一个命令。结果：

然后您可以探索路口：

> getVennRegion(myV, c('g1', 'g2', 'g4'))
[1] "NM_000139" "NM_000173" "NM_000208" "NM_000316" "NM_000318" "NM_000450" "NM_000539"

有vignette，其中包含更多信息。