如何在堆叠条形图中添加样本号，并检查R中的意义？

Question

我有一个dataframe df，如下所示：

df <- structure(list(Samples = c("sample1", "sample2", "sample3", "sample4", 
"sample5", "sample6", "sample7", "sample8", "sample9", "sample10", 
"sample11", "sample12", "sample13", "sample14", "sample15", "sample16", 
"sample17", "sample18", "sample19", "sample20", "sample21", "sample22", 
"sample23", "sample24", "sample25", "sample26", "sample27", "sample28", 
"sample29", "sample30", "sample31", "sample32", "sample33", "sample34", 
"sample35", "sample36", "sample37", "sample38", "sample39", "sample40", 
"sample41", "sample42"), new = c("Clus1", "Clus1", "Clus1", "Clus1", 
"Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", 
"Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", 
"Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", "Clus1", 
"Clus1", "Clus1", "Clus1", "Clus2", "Clus2", "Clus2", "Clus2", 
"Clus2", "Clus2", "Clus2", "Clus2", "Clus2", "Clus2", "Clus2", 
"Clus2", "Clus2", "Clus2"), Groups = c("GroupB", "GroupF", "GroupC", 
"GroupD", "GroupF", "GroupD", "GroupA", "GroupC", "GroupE", "GroupD", 
"GroupB", "GroupE", "GroupF", "GroupC", "GroupC", "GroupC", "GroupA", 
"GroupA", "GroupA", "GroupE", "GroupC", "GroupB", "GroupC", "GroupC", 
"GroupF", "GroupB", "GroupF", "GroupF", "GroupE", "GroupA", "GroupD", 
"GroupE", "GroupF", "GroupB", "GroupD", "GroupD", "GroupE", "GroupE", 
"GroupD", "GroupD", "GroupE", "GroupD")), row.names = c(NA, -42L
), class = c("tbl_df", "tbl", "data.frame"))

利用上述数据，我绘制了一个叠加条形图：

group.colors <- c("GroupA"="skyblue","GroupB"="brown", "GroupC"="purple", "GroupD"="darkblue",
                  "GroupE"="darkgreen", "GroupF"="#FF8D00")
ggplot(df,aes(x = new,fill = Groups)) + 
  geom_bar() +
  scale_fill_manual(values=group.colors)

这个数字如下：

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1. 如何在数字上添加Clus1和Clus2中每个组的示例号？

、

1. 、GroupE和GroupF都可以在Clus1和Clsu2中看到。那么，如何检查他们的交往呢？有这样的例子吗？

Answer 1

您可以添加如下示例编号：

ggplot(df,aes(x = new,fill = Groups)) + 
  geom_bar() +
  geom_text(stat = "count", aes(label = ..count..), color = "white", 
            position = position_stack(vjust = 0.5)) +
  scale_fill_manual(values=group.colors)

​

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第二个问题还不是很清楚，但是你可以用Fisher的精确测试来检查E和F在这两个集群中的比例是否有很大的不同--也许这就是你的意思？

fisher.test(with(df[df$Groups %in% c("GroupE", "GroupF"),], table(Groups, new)))
#> 
#>  Fisher's Exact Test for Count Data
#> 
#> data:  with(df[df$Groups %in% c("GroupE", "GroupF"), ], table(Groups, new))
#> p-value = 0.1189
#> alternative hypothesis: true odds ratio is not equal to 1
#> 95 percent confidence interval:
#>  0.001827082 1.768053629
#> sample estimates:
#> odds ratio 
#>  0.1189474