如何在 R ggplot2 中导出正确缩放的热图和树状图

Question

我正在尝试这个（https://jcoliver.github.io/learn-r/008-ggplot-dendrograms-and-heatmaps.html）教程，使用ggplot2制作热图和树状图。数据可以在这里找到：https://jcoliver.github.io/learn-r/data/otter-mandible-data.csv.

但是，当我尝试导出高分辨率图像时，

jpeg(file="HeatDendoTest02.jpeg", units="mm", width=775, height=638, res=300)
grid.newpage()
print(heatmap_plot, 
      vp = viewport(x = 0.4, y = 0.5, width = 0.8, height = 1.0))
print(dendro_plot, 
      vp = viewport(x = 0.90, y = 0.43, width = 0.2, height = 0.92))
dev.off()

树状图的排列与热图不合适，我想知道如何解决这个问题。

# Cluster & heatmap on otter data
# Jeff Oliver
# [email protected]
# 2017-08-15

################################################################################

# Load dependencies
library("ggplot2")
library("ggdendro")
library("tidyr")
library("grid")

# Read in data
otter <- read.csv(file = "data/otter-mandible-data.csv",
                  stringsAsFactors = TRUE)

# Restrict the data to only two species, A. cinerea & L. canadensis
two_species <- c("A. cinerea", "L. canadensis")
otter <- otter[otter$species %in% two_species, ]

# Force re-numbering of the rows after subsetting
rownames(otter) <- NULL

# Scale each measurement (independently) to have a mean of 0 and variance of 1
otter_scaled <- otter
otter_scaled[, c(4:9)] <- scale(otter_scaled[, 4:9])

# Run clustering
otter_matrix <- as.matrix(otter_scaled[, -c(1:3)])
rownames(otter_matrix) <- otter_scaled$accession
otter_dendro <- as.dendrogram(hclust(d = dist(x = otter_matrix)))

# Create dendrogram plot
dendro_plot <- ggdendrogram(data = otter_dendro, rotate = TRUE) + 
  theme(axis.text.y = element_text(size = 6))

# Heatmap

# Data wrangling
otter_long <- pivot_longer(data = otter_scaled,
                           cols = -c(species, museum, accession),
                           names_to = "measurement",
                           values_to = "value")
# Extract the order of the tips in the dendrogram
otter_order <- order.dendrogram(otter_dendro)
# Order the levels according to their position in the cluster
otter_long$accession <- factor(x = otter_long$accession,
                               levels = otter_scaled$accession[otter_order], 
                               ordered = TRUE)

# Create heatmap plot
heatmap_plot <- ggplot(data = otter_long, aes(x = measurement, y = accession)) +
  geom_tile(aes(fill = value)) +
  scale_fill_gradient2() +
  theme(axis.text.y = element_blank(),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank(),
        legend.position = "top")

# All together
grid.newpage()
print(heatmap_plot, 
      vp = viewport(x = 0.4, y = 0.5, width = 0.8, height = 1.0))
print(dendro_plot, 
      vp = viewport(x = 0.90, y = 0.43, width = 0.2, height = 0.92))

导出绘图后，树状图与热图不匹配。

Answer 1

这里有一个选项，使用

patchwork

在导出之前将绘图粘合在一起。尽管如此，将树状图与热图对齐仍然需要一些额外的工作，即我们需要使用

scale_x_continuous

对 y 尺度进行相同的扩展（

x

，因为

rotate=TRUE

）。此外，这样做时我们还必须设置

breaks=

和

labels=

.

注意：我使用

ggsave

进行导出并设置

scale=.33

以使文本可读。

library(ggplot2)
library(patchwork)

dendro_plot <- dendro_plot +
  scale_x_continuous(
    breaks = seq_along(levels(otter_long$accession)),
    labels = levels(otter_long$accession),
    # Set the same expansion as for the heatmap
    expand = c(0, .6)
  )

heatmap_plot + dendro_plot +
  plot_layout(widths = c(.8, .2))

ggsave(
  "HeatDendoTest02.jpeg",
  units = "mm", width = 775,
  height = 638, dpi = 300,
  scale = .33
)