用R中的置信区间绘制相关数据帧

是否有方法在

ggplot（）

中将具有上下置信区间的数据帧绘制为相关矩阵？

我可以使用

ggplot（）

强制执行相关“矩阵”排序，如下所示：

指定数据帧：

phen1<-c("Activity", "Aggression", "PC1", "PC2", "Activity", "Aggression")
phen2<-c("Aggression",  "PC1",         "PC2", "Activity", "PC1",     "PC2")
cors<-c(0.06,            -0.003,        -0.04, -0.001,   -0.003,      0.004)
upper<-c(0.10,          0.01,       0.002, 0.02,        0.02,       0.02)
lower<-c(0.03,          -0.01,      -0.08, -0.02,       -0.01,  -0.02)
data<- data.frame(phen1, phen2, cors, upper, lower)

> data
       phen1      phen2   cors upper lower
1   Activity Aggression  0.060 0.100  0.03
2 Aggression        PC1 -0.003 0.010 -0.01
3        PC1        PC2 -0.040 0.002 -0.08
4        PC2   Activity -0.001 0.020 -0.02
5   Activity        PC1 -0.003 0.020 -0.01
6 Aggression        PC2  0.004 0.020 -0.02

这提供了我所需要的，但它不是一个非常优雅的解决方案，并且涉及大量的

annotate（）

---

有没有人建议我如何在

ggplot（）中用上下置信区间作为相关矩阵来绘制数据帧

？

也许您可以将置信区间字符串添加到

熔化的\u corr

数据对象中，并在第二行

geom\u文本中使用它们，同时还可以使用
vjust
调整ci字符串的垂直位置

melted_corr$ci <- c("(0.03, 0.10)","(-0.01, 0.02)","(-0.02, 0.02)","(-0.01, 0.01)","(-0.02, 0.02)", "(-0.08, 0.002)")

ggplot(data = melted_corr, aes(x=phen, y=variable, fill=value)) + 
  geom_tile(color = "white")+
  #add a colour gradient to specify which values are larger
  scale_fill_gradient2(low = "gray40", high = "gray40", mid = "white", 
                       midpoint = 0, limit = c(-0.10,0.10), 
                       name="Robust\ncorrelation") + 
  theme_minimal()+ 
  coord_fixed()+
  scale_y_discrete(position = "right")+
  geom_text(aes(phen, variable, label = value), color = "black", size = 7) +
  geom_text(aes(phen, variable, label = ci), color = "black", size = 5,
            vjust = 2.5) + # ci labels added here
  labs(y="", x="")+
  theme(axis.line = element_line(colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text=element_text(size = 15), #changes size of axes #s 
        axis.title=element_text(size= 15), #changes size of axes labels 
        text = element_text(size = 17), 
        legend.position = c(0.15,0.8), #move legend into plot
        legend.title=element_blank())+
  #add symbols to specify significance manually
  annotate("text", x = 1.2, y = 1, label = "*", size = 7)+
  annotate("text", x = 3.22, y = 3, label = "*", size = 7)

melled_corr$ci我认为您可以对原始数据进行不同的重塑，因为这会让您在绘图阶段有太多的工作要做。您可以执行以下操作，而不是所有的扩散和融化：

#复制数据，但前两列已切换
数据2硬编码的
[2:1，3:5]
可能无法概括或可读。我也看到你呆在
base
而不是
dplyr
争吵。可能希望保持与OP相同的样式。是否可以对代码进行更多的注释？我不理解
bigdata
符号，特别是
setNames（data[c（2:1，3:5）]
和
paste0
）
get_lower_tri<-function(corrdata){
  corrdata[upper.tri(corrdata)] <- NA
  return(corrdata)
}

lower_tri <- get_lower_tri(corrdata)
melted_corr <- melt(lower_tri, na.rm = TRUE)

ggplot(data = melted_corr, aes(x=phen, y=variable, fill=value)) + 
  geom_tile(color = "white")+
#add a colour gradient to specify which values are larger
  scale_fill_gradient2(low = "gray40", high = "gray40", mid = "white", 
                       midpoint = 0, limit = c(-0.10,0.10), 
                       name="Robust\ncorrelation") + 
  theme_minimal()+ 
  coord_fixed()+
  scale_y_discrete(position = "right")+
  geom_text(aes(phen, variable, label = value), color = "black", size = 7) +
  labs(y="", x="")+
  theme(axis.line = element_line(colour = "black"),
          panel.grid.major = element_blank(),
          panel.grid.minor = element_blank(),
          panel.border = element_blank(),
          panel.background = element_blank(),
          axis.text=element_text(size = 15), #changes size of axes #s 
          axis.title=element_text(size= 15), #changes size of axes labels 
          text = element_text(size = 17), 
          legend.position = c(0.15,0.8), #move legend into plot
          legend.title=element_blank())+
#add CI values manually
  annotate("text", x = 1, y = 0.75, label = "(0.03, 0.10)", size = 5)+
  annotate("text", x = 2, y = 0.75, label = "(-0.01, 0.02)", size = 5)+
  annotate("text", x = 2, y = 1.75, label = "(-0.01, 0.01)", size = 5)+
  annotate("text", x = 3, y = 0.75, label = "(-0.02, 0.02)", size = 5)+
  annotate("text", x = 3, y = 1.75, label = "(-0.02, 0.02)", size = 5)+
  annotate("text", x = 3, y = 2.75, label = "(-0.08, 0.002)", size = 5)+
#add symbols to specify significance manually
  annotate("text", x = 1.2, y = 1, label = "*", size = 7)+
  annotate("text", x = 3.22, y = 3, label = "*", size = 7)

melted_corr$ci <- c("(0.03, 0.10)","(-0.01, 0.02)","(-0.02, 0.02)","(-0.01, 0.01)","(-0.02, 0.02)", "(-0.08, 0.002)")

ggplot(data = melted_corr, aes(x=phen, y=variable, fill=value)) + 
  geom_tile(color = "white")+
  #add a colour gradient to specify which values are larger
  scale_fill_gradient2(low = "gray40", high = "gray40", mid = "white", 
                       midpoint = 0, limit = c(-0.10,0.10), 
                       name="Robust\ncorrelation") + 
  theme_minimal()+ 
  coord_fixed()+
  scale_y_discrete(position = "right")+
  geom_text(aes(phen, variable, label = value), color = "black", size = 7) +
  geom_text(aes(phen, variable, label = ci), color = "black", size = 5,
            vjust = 2.5) + # ci labels added here
  labs(y="", x="")+
  theme(axis.line = element_line(colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text=element_text(size = 15), #changes size of axes #s 
        axis.title=element_text(size= 15), #changes size of axes labels 
        text = element_text(size = 17), 
        legend.position = c(0.15,0.8), #move legend into plot
        legend.title=element_blank())+
  #add symbols to specify significance manually
  annotate("text", x = 1.2, y = 1, label = "*", size = 7)+
  annotate("text", x = 3.22, y = 3, label = "*", size = 7)