如何用R将多数据集合并到同一张散点图中？

完全可以用散点图实现三个数据集的合并展示，不需要更换图表类型，只需要通过区分数据来源的视觉特征（比如点的形状、额外分组标识），就能在同一张图里清晰呈现三个数据集的差异。

数据概览 #

data 1 #

data 2 #

data 3 #

可复现代码（数据部分） #

# 生成三个数据集
data_1 <- structure(list(GO.term = c("BP", "MF", "CC", "KEGG"), 
                         Count = c(163L, 48L, 58L, 27L), 
                         Enrichment = c(0.008, 0.007, 0.008, 0.008), 
                         P.value = c(0.37, 0.33, 0.39, 0.43)), 
                    class = "data.frame", row.names = c(NA, 4L))

data_2 <- structure(list(GO.term = c("BP", "MF", "CC", "KEGG"), 
                         Count = c(167L, 50L, 50L, 23L), 
                         Enrichment = c(0.01, 0.008, 0.006, 0.01), 
                         P.value = c(0.31, 0.29, 0.34, 0.37)), 
                    class = "data.frame", row.names = c(NA, 4L))

data_3 <- structure(list(GO.term = c("BP", "MF", "CC", "KEGG"), 
                         Count = c(123L, 44L, 50L, 14L), 
                         Enrichment = c(0.009, 0.01, 0.007, 0.009), 
                         P.value = c(0.22, 0.22, 0.24, 0.28)), 
                    class = "data.frame", row.names = c(NA, 4L))

合并数据集并绘制散点图的实现代码 #

先给每个数据集添加分组标识，合并成一个数据框后，用点的形状区分不同数据集，同时保留原有的Count（点大小）和P.value（点颜色）映射：

library(ggplot2)
library(dplyr)

# 添加分组标识并合并数据
combined_data <- bind_rows(
  data_1 %>% mutate(Group = "data_1"),
  data_2 %>% mutate(Group = "data_2"),
  data_3 %>% mutate(Group = "data_3")
)

# 绘制合并后的散点图
ggplot(combined_data, aes(x = Enrichment, y = GO.term)) +
  geom_point(aes(size = Count, color = P.value, shape = Group), alpha = 0.8) +
  # 优化视觉效果
  scale_color_viridis_c(option = "plasma", name = "P value") +
  scale_size_continuous(name = "Gene Count") +
  scale_shape_manual(values = c(16, 17, 18), name = "Dataset") +
  labs(x = "Enrichment", y = "GO/KEGG Term", title = "Enrichment Analysis across 3 Datasets") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5))

补充优化方案 #

如果担心同位置点重叠影响观察，可以：

• 给点添加轻微位置偏移：geom_point(..., position = position_jitter(width = 0.0005))
• 降低点的透明度（已在代码中设置alpha=0.8）
• 若不需要严格在同一张图展示，也可以用分面图：+ facet_wrap(~Group)

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