如何取消列出字符串列以计算匹配项？

Question

我想计算 2 个数据集之间的任何匹配字符串。这是一个数据集，其中包含一列基因和另一列与这些基因相互作用的基因。

例如：

#dataset1
Gene    Interactors
ACE     BRCA2, NOS2, SEPT9
HER2    AGT, TGRF
YUO     SEPT9, NOS2, TET2

我有第二个数据集也有类似的基因和相互作用的基因。例如：

#dataset2
Gene    Interactors
RTY     ADFD, NOS3, SEPT9
TERT    ADAM2, GERP
GHJ     TET2, NOS2

我希望能够计算数据集 1 中有多少 Interactors 与数据集 2 中的匹配 Interactors。

示例输出：

Gene    Interactors          Secondary_interaction_count
ACE     BRCA2, NOS2, SEPT9            2 #SEPT9 and NOS2 are in the 2nd dataset under interacting genes
HER2    AGT, TGRF                     0 
YUO     SEPT9, ADAM2, TET2            3 #all 3 are in dataset 2

目前我有 2 个版本可以尝试获取它。一个只给出真假的我不知道怎么改成计数：

temp <- unlist(strsplit(df2$interactors, ', '))
df1$secondary_count <- sapply(strsplit(df1$interactors, ', '), 
                                                 function(x) any(x %in% temp))

还有一个我认为没有拆分字符串，但我不确定如何修改它：

df1 %>%
  mutate(secondary_count = str_count(interactors, str_c(df2$interactors, collapse = '|')))

有没有办法修改这两种编码尝试中的任何一种以获得计数？或者我应该尝试其他方法？

输入数据：

#df1:
structure(list(Gene = c("ACE", "HER2", "YUO"), Interactors = c("BRCA2, NOS2, SEPT9", 
"AGT, TGRF", "SEPT9, NOS2, TET2")), row.names = c(NA, -3L), class = c("data.table", 
"data.frame"))

#df2:
structure(list(Gene = c("RTY", "TERT", "GHJ"), Interactors = c("ADFD, NOS3, SEPT9", 
"ADAM2, GERP", "TET2, NOS2")), row.names = c(NA, -3L), class = c("data.table", 
"data.frame"))

> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252 
[2] LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] sqldf_0.4-11      RSQLite_2.2.1     gsubfn_0.7        proto_1.0.0      
 [5] forcats_0.5.0     stringr_1.4.0     purrr_0.3.4       readr_1.4.0      
 [9] tidyr_1.1.2       tibble_3.0.4      ggplot2_3.3.2     tidyverse_1.3.0  
[13] plyr_1.8.6        dplyr_1.0.2       data.table_1.13.2

loaded via a namespace (and not attached):
 [1] gtools_3.8.2     tidyselect_1.1.0 haven_2.3.1      tcltk_4.0.2     
 [5] colorspace_1.4-1 vctrs_0.3.4      generics_0.0.2   chron_2.3-56    
 [9] blob_1.2.1       rlang_0.4.8      pillar_1.4.6     glue_1.4.1      
[13] withr_2.3.0      DBI_1.1.0        bit64_4.0.5      dbplyr_1.4.4    
[17] modelr_0.1.8     readxl_1.3.1     lifecycle_0.2.0  munsell_0.5.0   
[21] gtable_0.3.0     cellranger_1.1.0 rvest_0.3.6      memoise_1.1.0   
[25] fansi_0.4.1      broom_0.7.2      Rcpp_1.0.5       scales_1.1.1    
[29] backports_1.1.10 jsonlite_1.7.1   fs_1.5.0         bit_4.0.4       
[33] hms_0.5.3        digest_0.6.27    stringi_1.5.3    grid_4.0.2      
[37] cli_2.1.0        tools_4.0.2      magrittr_1.5     crayon_1.3.4    
[41] pkgconfig_2.0.3  ellipsis_0.3.1   xml2_1.3.2       reprex_0.3.0    
[45] lubridate_1.7.9  assertthat_0.2.1 httr_1.4.2       rstudioapi_0.11 
[49] R6_2.4.1         compiler_4.0.2

Answer 1

试试这个

library(tidyr)
library(dplyr)

sep_rows <- . %>% separate_rows(Interactors, sep = ", ")

df1 %>% 
  sep_rows() %>% 
  mutate(
    found = !is.na(match(Interactors, sep_rows(df2)$Interactors))
  ) %>% 
  group_by(Gene) %>% 
  summarise(
    Interactors = toString(Interactors), 
    Secondary_interaction_count = sum(found)
  )

输出

`summarise()` ungrouping output (override with `.groups` argument)
# A tibble: 3 x 3
  Gene  Interactors        Secondary_interaction_count
  <chr> <chr>                                    <int>
1 ACE   BRCA2, NOS2, SEPT9                           2
2 HER2  AGT, TGRF                                    0
3 YUO   SEPT9, NOS2, TET2                            3

Answer 2

再试一次：

> df1 %>% separate_rows(Interactors) %>% rowwise() %>% 
+   mutate(secondary_interactions = str_extract_all(Interactors, paste0(df2 %>% separate_rows(Interactors) %>% pull(Interactors), collapse = '|'))) %>% 
+   unnest(secondary_interactions, keep_empty = T) %>% group_by(Gene) %>% 
+   mutate(Interactors = toString(Interactors), secondary_interactions_cnt = case_when(is.na(secondary_interactions) ~ 0, TRUE ~ 1)) %>% 
+   mutate(secondary_interactions = sum(secondary_interactions_cnt)) %>% select(-4)%>% distinct()
# A tibble: 3 x 3
# Groups:   Gene [3]
  Gene  Interactors        secondary_interactions
  <chr> <chr>                               <dbl>
1 ACE   BRCA2, NOS2, SEPT9                      2
2 HER2  AGT, TGRF                               0
3 YUO   SEPT9, NOS2, TET2                       3
>

如何取消列出字符串列以计算匹配项？

How to unlist column of strings to count matches?

r

strsplit

dplyr