Question

使用下面的data.frame

数据

df <- read.table(text = c("
NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA
                          0.4748    NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA
                          0.905 0.5362  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA
                          0.0754    0.0118  0.0614  NA  NA  NA  NA  NA  NA  NA  NA  NA
                          0.8768    0.3958  0.7952  0.1034  NA  NA  NA  NA  NA  NA  NA  NA
                          0.5708    0.2056  0.4984  0.2356  0.6736  NA  NA  NA  NA  NA  NA  NA
                          0.2248    0.6204  0.268   0.0014  0.183   0.0768  NA  NA  NA  NA  NA  NA
                          0.483 0.9824  0.5314  0.0114  0.3906  0.1968  0.6308  NA  NA  NA  NA  NA
                          0.697 0.732   0.7604  0.0264  0.594   0.3334  0.416   0.7388  NA  NA  NA  NA
                          0.2918    0.7286  0.3382  0.003   0.2386  0.1122  0.8712  0.7266  0.509   NA  NA  NA
                          0.5904    0.8352  0.6704  0.0188  0.4966  0.273   0.5192  0.8328  0.8736  0.5914  NA  NA
                          0.3838    0.8768  0.4476  0.0042  0.3148  0.1498  0.7288  0.873   0.6178  0.8276  0.7432  NA
                          "), header = F)

colnames(df) <- c( "TK1",   "TK2",  "TK3",  "TK4"   , "TK5",    "TK6",  "TK7",  "TK8",  "TK9",  "TK10", "TK11", "TK12")
rownames(df) <- c( "TK1",   "TK2",  "TK3",  "TK4"   , "TK5",    "TK6",  "TK7",  "TK8",  "TK9",  "TK10", "TK11", "TK12")

df
#        TK1    TK2    TK3    TK4    TK5    TK6    TK7    TK8    TK9   TK10   TK11 TK12
#TK1      NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA   NA
#TK2  0.4748     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA   NA
#TK3  0.9050 0.5362     NA     NA     NA     NA     NA     NA     NA     NA     NA   NA
#TK4  0.0754 0.0118 0.0614     NA     NA     NA     NA     NA     NA     NA     NA   NA
#TK5  0.8768 0.3958 0.7952 0.1034     NA     NA     NA     NA     NA     NA     NA   NA
#TK6  0.5708 0.2056 0.4984 0.2356 0.6736     NA     NA     NA     NA     NA     NA   NA
#TK7  0.2248 0.6204 0.2680 0.0014 0.1830 0.0768     NA     NA     NA     NA     NA   NA
#TK8  0.4830 0.9824 0.5314 0.0114 0.3906 0.1968 0.6308     NA     NA     NA     NA   NA
#TK9  0.6970 0.7320 0.7604 0.0264 0.5940 0.3334 0.4160 0.7388     NA     NA     NA   NA
#TK10 0.2918 0.7286 0.3382 0.0030 0.2386 0.1122 0.8712 0.7266 0.5090     NA     NA   NA
#TK11 0.5904 0.8352 0.6704 0.0188 0.4966 0.2730 0.5192 0.8328 0.8736 0.5914     NA   NA
#TK12 0.3838 0.8768 0.4476 0.0042 0.3148 0.1498 0.7288 0.8730 0.6178 0.8276 0.7432   NA

我无法更改输入数据。我将继续以这种格式使用不同的变量，每次都基于用户。

我使用下面的代码创建了一个新变量Relationship，以便将df从宽格式转换为长格式，然后排列Relation1和Relationship个变量的级别，这要归功于akrun's answer to this question。最后，我创建了热图，如下所示

trial <- df
trial$Relationship <- rownames(df) 
trial1 <- subset(trial, select = c(13, 1, 2, 3,4,5,6,7,8,9,10,11,12))

df2 <- gather(trial1, "Relation1", "Strength", 2:13)

df2 <- df2 %>% 
  dplyr::mutate(Strength1 = round(Strength, digits = 2))%>% 
  dplyr::select(Relationship,Relation1, Strength1 )

df3 <- df2 %>% 
  extract(Relationship, into = c("Relationship1", "Relationship2"), "(\\D+)(\\d+)",
          remove = FALSE, convert=TRUE) %>% 
  mutate(Relationship = factor(Relationship, levels = paste0(Relationship1[1], 
                                                             min(Relationship2):max(Relationship2)))) %>% 
  select(-Relationship1, -Relationship2) %>% 
  extract(Relation1, into = c("Relation11", "Relation12"), "(\\D+)(\\d+)",
          remove = FALSE, convert=TRUE) %>% 
  mutate(Relation1 = factor(Relation1, levels = paste0(Relation11[1], 
                                                       min(Relation12):max(Relation12)))) %>% 
  select(-Relation11, -Relation12) 


df3$Relation1 = with(df3, factor(Relation1, levels = rev(levels(Relation1))))


ggheatmap <- ggplot(df3, aes(Relationship, Relation1,  fill = Strength1))+
  geom_tile(color = "white")+
  scale_fill_gradient2(low = "red", high = "green", mid = "lightgreen", 
                       midpoint = 0.5, limit = c(0,1), space = "Lab", 
                       name="Correlation") + theme_minimal()

ggheatmap + 
  geom_text(aes(Relationship, Relation1, label = Strength1), color = "black", size = 4) +
  labs(x = expression(""), 
       y=expression(""))

RESULT

问题

我想制作热图的动态图。那么，无论变量和观察的数量如何，都可以绘制热图而无需为不同数量的变量更改代码？

有没有这样做？

Answer 1

在这种情况下，我感觉你的方法迂回（我提到heatmap with values (ggplot2)）。这段代码只需要colnames（df）和rownames（df）。

library(reshape2); library(ggplot2)

df2 <- melt(as.matrix(df), id.var = names(df)[1])    # as.matrix() fixes colnames of long df.
df2$Var2 <- with(df2, factor(Var2, levels=rev(levels(Var2))))

ggheatmap <- ggplot(df2, aes(Var1, Var2, fill=value)) +
  geom_tile(color = "white")+
  scale_fill_gradient2(low = "red", high = "green", mid = "lightgreen", 
                       midpoint = 0.5, limit = c(0,1), space = "Lab", 
                       name="Correlation") + theme_minimal()

ggheatmap + 
  geom_text(aes(label = round(value, 2)), color = "black", size = 4) + 
  labs(x = expression(""), y=expression(""))

Answer 2

library(ggplot2)
library(tidyr)
library(dplyr)

无论列数和行数

，此代码块都能正常工作

df <-
  df %>%
  mutate(Relationship = rownames(.)) %>% #Replaces trial$Relationship <- rownames(df) 
  select(Relationship, everything()) %>% #Replaces trial1 <- subset(trial, select = c(13, 1, 2, 3,4,5,6,7,8,9,10,11,12))
  gather('Relation1', 'Strength', -1) %>% #Replaces df2 <- gather(trial1, "Relation1", "Strength", 2:13)
  mutate(Strength = round(Strength, digits = 2))

下面的代码块是获取列

的因子水平的更简洁方法

# Order Relatinoship variables by numeric suffix
# Since its a square matrix you only have to do it once for both columns

factorLevels <-
  df %>%
  select(Relationship) %>%
  distinct() %>%
  extract(Relationship, into = c("TK", "num"), "(\\D+)(\\d+)",
          remove = FALSE, convert=TRUE) %>%
  arrange(num) %>%
  select(Relationship)

df <-
  df %>%
  mutate(Relationship = factor(Relationship, levels = factorLevels$Relationship),
         Relation1 = factor(Relation1, levels = rev(factorLevels$Relationship)))

修改后的绘图代码

ggheatmap <- ggplot(df, aes(Relationship, Relation1,  fill = Strength))+
  geom_tile(color = "white")+
  scale_fill_gradient2(low = "red", high = "green", mid = "lightgreen", 
                       midpoint = 0.5, limit = c(0,1), space = "Lab", 
                       name="Correlation") + theme_minimal()

ggheatmap + 
  geom_text(aes(Relationship, Relation1, label = Strength), color = "black", size = 4) +
  labs(x = expression(""), 
       y=expression(""))

ggplot：如何绘制热图而不管变量的数量

2 个答案: