维恩图5路(用' venn‘R)

Question

首先，我想为我的基本问题道歉。我确信，如果我是一个经验丰富的用户，在这个主题上的其他线程将是令人满意的，但我无法管理，即使是在阅读他们。所以如果这可能会惹恼你，欢迎你忽略。

对于那些仍然想要帮助的人:我正在尝试创建一个5路venn图。我的数据以excel格式排列为5列(每个列代表一个站点the )，每个列代表5个站点的物种丰富度(0-16)。

我想要创建一个很好的venn图，类似于这样：https://i.stack.imgur.com/TeRSJ.png

我相信它只需点击几下就可以了。但是我无法做到:以写的方式加载我的数据--它应该是哪种格式？数据集？名单？矩阵？

我认为R似乎暗示我只能使用存在缺勤数据(0/1)，对吗？

最后，我想我会使用这个命令，并将x作为我的数据

venn(x, snames = c(""), ilabels = FALSE, counts = FALSE, zcolor = c("bw"),
transparency = 0.3, ellipse = FALSE, size = 15, cexil = 0.45, cexsn = 0.85, 
...)

有人能告诉我该用什么代码吗？我也可以上传我的数据集，如果有人告诉我如何在这里这样做。

提前感谢

Answer 1

免责声明1:我不确定您的问题是关于如何计算每个子组的计数，或者如何绘制5组Venn图。我猜是后者。

免责声明2:我发现5组文恩图极难阅读.到了无用的地步。但这是我个人的看法。

如果其他R包是一个选项，下面是一个使用VennDiagram (直接来自VennDiagram参考手册)的经过改进的5集示例

library(VennDiagram);
venn.plot <- draw.quintuple.venn(
    area1 = 301, area2 = 321, area3 = 311, area4 = 321, area5 = 301,
    n12 = 188, n13 = 191, n14 = 184, n15 = 177,
    n23 = 194, n24 = 197, n25 = 190,
    n34 = 190, n35 = 173, n45 = 186,
    n123 = 112, n124 = 108, n125 = 108,
    n134 = 111, n135 = 104, n145 = 104,
    n234 = 111, n235 = 107, n245 = 110,
    n345 = 100,
    n1234 = 61, n1235 = 60, n1245 = 59,
    n1345 = 58, n2345 = 57,
    n12345 = 31,
    category = c("A", "B", "C", "D", "E"),
    fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
    cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
    cat.cex = 2,
    margin = 0.05,
    cex = c(
        1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
        1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
    ind = TRUE);

png("venn_5set.png");
grid.draw(venn.plot);
dev.off();

​

​

2017年11月15日最新情况

源表采用非典型格式。正如我在注释中解释的，您通常以二进制矩阵(每组一列、0或1所指示的每个观察的成员资格)或set元素列表开始。

老实说，我越来越不确定你到底想做什么。我有一种感觉，可能会对文恩图产生误解。例如，让我们看一看表的第一行

# Read data
library(readxl);
data <- as.data.frame(read_excel("~/Downloads/dataset4venn.xlsx"));
rownames(data) <- data[, 1];
data <- data[, -1];
head(data);
#  A B  C D  E
#1 8 8  7 8 10
#2 0 0 10 0  2
#3 0 0  0 0  3
#4 0 0  1 2  0
#5 1 0  1 0  2
#6 0 0  0 0  1    

观察是指某一特定组(即取样点)中存在(由1编码)或(由0编码)存在的唯一元素(在您的例子中是物种)。你所称的目击次数在这里并不重要:文恩图探讨了在不同地点取样的不同物种之间的逻辑关系，或者换句话说，哪些独特的物种是由A-E站点共享的。

尽管如此，忽略了每个站点的目击次数，您可以在下面的5组Venn图中显示不同站点之间的重叠。我首先定义一个帮助函数cts来计算每个组/重叠的计数，然后将这些数字输入draw.quintuple.venn。

# Function to calculate the count per group/overlap
# Note: data is a global variable
cts <- function(set) {
    df <- data;
    for (i in 1:length(set)) df <- subset(df, df[set[i]] >= 1);
    nrow(df);
}

# Plot
library(VennDiagram);
venn.plot <- draw.quintuple.venn(
    area1 = cts("A"), area2 = cts("B"), area3 = cts("C"),
    area4 = cts("D"), area5 = cts("E"),
    n12 = cts(c("A", "B")), n13 = cts(c("A", "C")), n14 = cts(c("A", "D")),
    n15 = cts(c("A", "E")), n23 = cts(c("B", "C")), n24 = cts(c("B", "D")),
    n25 = cts(c("B", "E")), n34 = cts(c("C", "D")), n35 = cts(c("C", "E")),
    n45 = cts(c("D", "E")),
    n123 = cts(c("A", "B", "C")), n124 = cts(c("A", "B", "D")),
    n125 = cts(c("A", "B", "E")), n134 = cts(c("A", "C", "D")),
    n135 = cts(c("A", "C", "E")), n145 = cts(c("A", "D", "E")),
    n234 = cts(c("B", "C", "D")), n235 = cts(c("B", "C", "E")),
    n245 = cts(c("B", "D", "E")), n345 = cts(c("C", "D", "E")),
    n1234 = cts(c("A", "B", "C", "D")), n1235 = cts(c("A", "B", "C", "E")),
    n1245 = cts(c("A", "B", "D", "E")), n1345 = cts(c("A", "C", "D", "E")),
    n2345 = cts(c("B", "C", "D", "E")),
    n12345 = cts(c("A", "B", "C", "D", "E")),
    category = c("A", "B", "C", "D", "E"),
    fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
    cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
    cat.cex = 2,
    margin = 0.05,
    cex = c(
        1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
        1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
    ind = TRUE);

png("venn_5set.png");
grid.draw(venn.plot);
dev.off();

​

​

PS

各种R包/internet源提供基于例如二进制矩阵或集合元素列表来计算重叠的辅助功能。例如，R/生物导体包limma提供了一个基于二进制矩阵计算所有重叠计数的函数limma::vennCounts。因此，如果您不想编写自己的函数(就像我一样)，您也可以使用这些函数。无论哪种方法，对于更复杂的Venn图，我建议不要手工计算重叠，因为这很容易出错(见您的错误消息)。

Answer 2

你好，莫蒂斯，我试过你发的剧本。我计算了excel中的重叠，最终得到：

library(VennDiagram);
venn.plot <- draw.quintuple.venn(
  area1 = 104, area2 = 120, area3 = 117, area4 = 158, area5 = 107,
  n12 = 59, n13 = 39, n14 = 55, n15 = 41,
  n23 = 48, n24 = 71, n25 = 48,
  n34 = 53, n35 = 53, n45 = 62,
  n123 = 30, n124 = 44, n125 = 35,
  n134 = 34, n135 = 30, n145 = 38,
  n234 = 42, n235 = 35, n245 = 44,
  n345 = 40, n1234 = 28, n1235 = 25, n1245 = 33,
  n1345 = 27, n2345 = 32,
  n12345 = 24,
  category = c("A", "B", "C", "D", "E"),
  fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
  cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
  cat.cex = 2,
  margin = 0.05,
  cex = c(
    1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
    1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
  ind = TRUE);

png("venn_5set.png");
grid.draw(venn.plot);
dev.off();

但我有个错误：

Draw.quintuple.venn中的错误(area1= 104，area2 = 120，area3 = 117，area4 = 158 )：不可能: a17 <- n135 - a27 - a29 - a31产生负区域

哪个是a17？