Question

我在R中有一个数据表，看起来像：

Gene Population Color Coverage
A_1 PopA Blue 0.016
A_1 PopA Green 0.022
A_1 PopB Blue 0.1322
A_1 PopB Green 0.552
A_2 PopA Blue 0.13
A_2 PopA Green 0.14
A_2 PopB Blue 1
A_2 PopB Green 0.9

我想了解不同颜色（蓝色和绿色）之间的差异，但仅适用于相同的基因和种群。最终，我想输出一个看起来像这样的表：

Gene Population Coverage
A_1 PopA -0.006
A_1 PopB -0.4198
A_2 PopA -0.01
A_2 PopB 0.1

我一直在使用Rmisc中的summarySE（）函数来获取我在上面指示的平均值，但是不清楚如何计算类似值之间的差值。

谢谢！

Answer 1

一个带有dplyr的选项是

library(dplyr)

my.df %>% 
  group_by(Gene, Population) %>% 
  summarize(Coverage = Coverage[Color == "Blue"] - Coverage[Color == "Green"])

# A tibble: 4 x 3
# Groups:   Gene [?]
#   Gene  Population Coverage
#   <fct> <fct>         <dbl>
# 1 A_1   PopA       -0.00600
# 2 A_1   PopB       -0.420  
# 3 A_2   PopA       -0.01   
# 4 A_2   PopB        0.100

数据

my.df <- 
  structure(list(Gene = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("A_1", "A_2"), class = "factor"), 
                 Population = structure(c(1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L), .Label = c("PopA", "PopB"), class = "factor"), 
                 Color = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("Blue", "Green"), class = "factor"), 
                 Coverage = c(0.016, 0.022, 0.1322, 0.552, 0.13, 0.14, 1, 0.9)), class = "data.frame", row.names = c(NA, -8L))

取两个水平的因子变量之差，同时保留R中的其他因子变量

1 个答案: