计算和提取数据框中所有列中行内唯一元素/基因的出现

Question

我有非常大的 csv 文件，并在存在缺失数据中搜索独特的基因，以及它们的数量。我的数据如下

df <- data.frame(
      A = c("G1", "G2", "G3", "G4", "G5","G6","G7", "G8", "G9","G10"),
      B = c(1, 0, 1, 0, 1, 1, 1, 0, 0, 0),
      C = c(1, 0, 1, 0, 0, 0, 0, 1, 1, 0),
      D = c(1, 1, 0, 0, 0, 0, 0, 0, 0, 1),
      E = c(1, 1, 1, 1, 0, 0, 0, 0, 0, 0))

输出如下第一个是具有独特基因的数据框

df_uniq <- data.frame(
  A = c("G4", "G5","G6","G7", "G8", "G9","G10"),
  B = c(0, 1, 1, 1, 0, 0, 0),
  C = c(0, 0, 0, 0, 1, 1, 0),
  D = c(0, 0, 0, 0, 0, 0, 1),
  E = c(1, 0, 0, 0, 0, 0, 0))

感谢您的帮助谢谢！

Answer 1

一个

dplyr

解决方案：

library(dplyr)

df_uniq <- df %>%
  filter(rowSums(pick(-A)) == 1)

#      A B C D E
# 4   G4 0 0 0 1
# 5   G5 1 0 0 0
# 6   G6 1 0 0 0
# 7   G7 1 0 0 0
# 8   G8 0 1 0 0
# 9   G9 0 1 0 0
# 10 G10 0 0 1 0

df_uniq %>%
  summarise(across(-A, sum))

#   B C D E
# 1 3 2 1 1

Answer 2

一个

dplyr

解决方案

library(dplyr)
df %>%
   filter(if_any(-A))

 colSums(df_uniq[-1])
B C D E 
3 2 1 1