R中scale_fill_gradientn函数报错：向连续色阶传入离散值

报错原因 #

报错Discrete values supplied to continuous scale的核心问题是：你的number列是字符型（字符串），但scale_fill_gradientn是为连续数值型变量设计的颜色映射函数，两者类型不匹配，因此触发错误。报错信息里的"0"带引号，也直接佐证了这一点——如果是数值型，不会显示引号。

解决方案 #

1. 转换number列为数值型 #

在绘图前，先将number列强制转换为数值类型，使用as.numeric()函数：

# 转换数据类型（关键步骤）
data$number <- as.numeric(data$number)

如果转换时出现警告（比如数据中存在非数字字符），可以用which(!grepl("^\\d+$", data$number))定位异常值，清理后再执行转换。

2. 修复后的完整代码 #

将类型转换步骤加入原代码，同时可添加na.value参数处理转换中可能出现的缺失值：

library(ggplot2)

colors <- c("#f7f9cb", "#c7edc0", "#92e0c3", "#56d0d0", "#00bdde", "#00afef", "#539df4", "#9085e8", "#cd6ace", "#f54a9d", "#ff3d5e", "#f0550d", "#fc8d59")

# 转换number列为数值型
data$number <- as.numeric(data$number)

ggplot(data, aes(x = tm, y = characteristic, fill = number)) +
  geom_tile(color = "black", size = 0.2) +
  geom_text(aes(label = ifelse(number != 0, number, "")), size = 3) +
  scale_fill_gradientn(colors = colors, na.value = "white") + # 处理NA值
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1),
        panel.border = element_rect(color = "black", fill = NA, size = 1),
        axis.line = element_line(color = "black"),
        plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
        axis.title = element_text(face = "bold", size = 12),
        axis.text = element_text(size = 10, face = "bold"),
        legend.title = element_text(face = "bold", size = 12),
        legend.text = element_text(size = 10, face = "bold"),
        legend.box.background = element_rect(color = "black", size = 1)) +
  labs(title = "Heatmap of Amino Acid Properties vs Inter-TM",
       x = "Transmembrane Regions",
       y = "Properties",
       fill = "Number of \nResidual Pairs") +
  coord_fixed()

绘制热图的替代方法 #

方法1：使用pheatmap包（静态专业热图） #

pheatmap专为热图设计，适合矩阵形式的数据，需先将长格式数据转换为宽矩阵：

library(pheatmap)
library(tidyr)

# 转换为宽格式矩阵
heat_matrix <- pivot_wider(data, 
                           id_cols = characteristic, 
                           names_from = tm, 
                           values_from = number,
                           values_fill = 0) %>%
  column_to_rownames("characteristic") %>%
  as.matrix()

# 绘制热图
pheatmap(heat_matrix,
         color = colors,
         display_numbers = TRUE, # 显示单元格数值
         number_color = "black",
         border_color = "black",
         main = "Heatmap of Amino Acid Properties vs Inter-TM",
         fontsize_row = 10,
         fontsize_col = 10,
         treeheight_row = 0, # 关闭行聚类
         treeheight_col = 0) # 关闭列聚类

方法2：使用heatmaply包（交互式热图） #

适合需要鼠标悬停查看细节的场景，生成可交互的网页版热图：

library(heatmaply)
library(tidyr)

# 转换为宽格式矩阵
heat_matrix <- pivot_wider(data, 
                           id_cols = characteristic, 
                           names_from = tm, 
                           values_from = number,
                           values_fill = 0) %>%
  column_to_rownames("characteristic") %>%
  as.matrix()

# 绘制交互式热图
heatmaply(heat_matrix,
          colors = colors,
          showticklabels = c(TRUE, TRUE),
          main = "Heatmap of Amino Acid Properties vs Inter-TM",
          fontsize_row = 10,
          fontsize_col = 10)

内容的提问来源于stack exchange，提问作者Rohan Nath