使用patchwork合并pheatmap与ggplot图时顺序调换触发报错求助

问题描述 #

使用ggplot2和patchwork组合图形时，以下代码可正常生成输出：

(f5 | f2 | f3 | f4) / f1$gtable

但调换上下图形顺序后，运行以下代码会触发报错：

f1$gtable / (f5 | f2 | f3 | f4)

错误信息如下：

Error in e1 + e2 + plot_layout(ncol = 1): non-numeric argument to binary operator
Traceback:

1. `/.ggplot`(f1$gtable, (f5 | f2 | f3 | f4))

尝试给两边添加括号等方式仍无法解决问题，可复现代码如下：

可复现代码 #

# 创建测试矩阵
test = matrix(rnorm(200), 20, 10)
test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
colnames(test) = paste("Test", 1:10, sep = "")
rownames(test) = paste("Gene", 1:20, sep = "")
# 绘制热图
f1=pheatmap(test)

# 创建分组数据
group_df = data.frame(Groups=rep(c("Group1", "Group2"), c(5,5)))

# 箱线图2
int = c("Gene1", "Gene2","Gene3")
df1=t(test[rownames(test) %in% int,])
df1 = as.data.frame(df1)
df1$Mean = rowMeans(df1[,])
df1 = cbind(group_df, df1)
f2=ggboxplot(df1, x = "Groups", y = "Mean", color = "Groups")

# 箱线图3
int = c("Gene4", "Gene5","Gene6")
df1=t(test[rownames(test) %in% int,])
df1 = as.data.frame(df1)
df1$Mean = rowMeans(df1[,])
df1 = cbind(group_df, df1)
f3=ggboxplot(df1, x = "Groups", y = "Mean", color = "Groups")

# 箱线图4
int = c("Gene7", "Gene8","Gene9")
df1=t(test[rownames(test) %in% int,])
df1 = as.data.frame(df1)
df1$Mean = rowMeans(df1[,])
df1 = cbind(group_df, df1)
f4=ggboxplot(df1, x = "Groups", y = "Mean", color = "Groups")

# 箱线图5
int = c("Gene10", "Gene5","Gene1")
df1=t(test[rownames(test) %in% int,])
df1 = as.data.frame(df1)
df1$Mean = rowMeans(df1[,])
df1 = cbind(group_df, df1)
f5=ggboxplot(df1, x = "Groups", y = "Mean", color = "Groups")

解决方案 #

使用patchwork的wrap_elements()函数，将f1$gtable包装为patchwork可识别的标准元素后再进行组合：

library(patchwork)
wrap_elements(f1$gtable) / (f5 | f2 | f3 | f4)

原因解释 #

f1$gtable是pheatmap返回的gtable对象，而patchwork的/运算符默认针对ggplot对象或patchwork组合对象设计。当右侧是gtable时，patchwork可自动兼容处理；但当左侧是gtable、右侧是patchwork组合对象时，会触发/.ggplot方法的匹配错误——该方法要求左侧为ggplot/patchwork类型对象，而非gtable。通过wrap_elements()将gtable包装为patchwork标准元素后，即可正常执行上下组合逻辑。

内容的提问来源于stack exchange，提问作者user2110417