根据字符串 ID 对值求和

Sum values based on their string ID

我有一个由逗号分隔的字符串序列组成的数据框。例如:

df <- data.frame(patterns = c("CCDC127, HSF1, NDUFB9", "CCDC127, EXOC3, YIF1A", "EXOC3, NDUFB9, YIF1A"))
df
               patterns
1 CCDC127, HSF1, NDUFB9
2 CCDC127, EXOC3, YIF1A
3  EXOC3, NDUFB9, YIF1A

我有另一个数据框,其中每个字符串对应一个数值。例如:

df2 <- data.frame(strings = c("CCDC127", "HSF1", "NDUFB9", "EXOC3", "YIF1A"),
                   scores = c(10, 11, 12, 13, 14))
df2
  strings scores
1 CCDC127     10
2    HSF1     11
3  NDUFB9     12
4   EXOC3     13
5   YIF1A     14

我想根据第二个数据框中的值计算第一个数据框中每个模式的总和。例如:

patterns sum
1 CCDC127, HSF1, NDUFB9  33
2 CCDC127, EXOC3, YIF1A  37
3  EXOC3, NDUFB9, YIF1A  39

如果有任何指示和帮助解决这个问题,我将不胜感激。

谢谢! 奥尔哈

您可以将 strsplitsapplymatch 一起使用:

df$sum <- sapply(strsplit(df$patterns, ", "), 
                 function(x) sum(df2$scores[match(x, df2$strings)]))
df
#>                patterns sum
#> 1 CCDC127, HSF1, NDUFB9  33
#> 2 CCDC127, EXOC3, YIF1A  37
#> 3  EXOC3, NDUFB9, YIF1A  39

这是一个我确信会有超级智能应用解决方案的解决方案,但我会通过将 df table 转换为查找 table,然后加入来实现它和总结。

df %>%
  mutate(patterns2 = patterns) %>%
  separate(patterns2, paste("c", 1:3)) %>%
  pivot_longer(cols = paste("c", 1:3)) %>%
  #end of lookup creation, now join on
  right_join(df2, by = c("value" = "strings" )) %>%
  group_by(patterns) %>%
  summarise(scores = sum(scores))

1)将df2转换为适合与eval一起使用的命名列表L,然后对解析pattern形成的每个表达式求值用加号替换逗号后。

L <- with(df2, split(scores, strings))
transform(df, sums = sapply(parse(text = gsub(",", "+", patterns)), eval, L))

给予:

               patterns sums
1 CCDC127, HSF1, NDUFB9   33
2 CCDC127, EXOC3, YIF1A   37
3  EXOC3, NDUFB9, YIF1A   39

2) 另一种方法是从模式中提取单词,在 (1) 的 L 中查找它们,然后求和。

library(gsubfn)
transform(df, sums = sapply(strapply(patterns, "\w+", x ~ L[[x]]), sum))

我们可以在 mutate 调用中使用 tidyr::separaterowSums

library(dplyr)
library(tidyr)

df%>%mutate(
  sum = df %>% separate(col=patterns, sep=', +', into=paste0('pattern', 1:3))%>%
  rowwise()%>%
  mutate(across(everything(), ~df2$scores[df2$strings==.x]))%>%
  rowSums())

               patterns sum
1 CCDC127, HSF1, NDUFB9  33
2 CCDC127, EXOC3, YIF1A  37
3  EXOC3, NDUFB9, YIF1A  39