在R中基于长格式数据按样本-组汇总表型结果

现有如下长格式data.frame数据集：

sample  substance  phenotype  group
1       A          s          X
1       B          s          X
1       C          r          Y
1       D          s          Y
2       A          r          X
2       B          r          X
2       C          s          Y
2       D          s          Y
3       A          r          X
3       B          s          X
3       C          s          Y
3       D          s          Y

structure(list(sample = c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3), 
    substance = c("A", "B", "C", "D", "A", "B", "C", "D", "A", 
    "B", "C", "D"), phenotype = c("s", "s", "r", "s", "r", "r", 
    "s", "s", "r", "s", "s", "s"), group = c("X", "X", "Y", "Y", 
    "X", "X", "Y", "Y", "X", "X", "Y", "Y")), class = "data.frame", row.names = c(NA, 
-12L))

需求：按sample和group分组，若每组内phenotype列存在值"r"，则该组结果res为"r"，否则为"s"，期望输出：

sample  group  res
1       X      s
1       Y      r
2       X      r
2       Y      s
3       X      r
3       Y      s

尝试的dplyr代码（仅作用于每行而非分组）：

library(dplyr)

data %>%
 group_by(sample,group) %>%
 mutate(res = ifelse(grepl("r", phenotype), "r", "s")

原代码用mutate会给每行生成独立的res值，而我们需要对每组进行汇总计算，改用summarise即可实现需求：

library(dplyr)

data %>%
  group_by(sample, group) %>%
  summarise(res = ifelse(any(phenotype == "r"), "r", "s"), .groups = "drop")

代码说明 #

• group_by(sample, group)：按样本编号和组别完成分组
• any(phenotype == "r")：直接判断组内是否存在至少一个"r"值，比grepl更贴合当前数据的明确取值
• summarise：将每组汇总为单行结果，生成目标res列
• .groups = "drop"：取消分组状态，输出普通的data.frame结构

运行上述代码即可得到期望的输出结果。

内容的提问来源于stack exchange，提问作者Haakonkas