根据 R 列中的部分字符串匹配创建新变量

Question

我有一个大的 df，其中包含以下列：“基因、变量、值”，我想向其中添加一个新变量“light_exposure”。要将值分配给这个新列，我想查看变量列中是否存在“i13”的部分字符串匹配，并在“light_exposure”列中相应地分配“yes”或“no”值。

“变量”列包含主题 ID，典型的 ID 类似于“sem_outdir_NAi13t3n27_S4”

这是我认为可行的代码。然而，即使不存在匹配项，它也会在新列中分配“是”。

df_long <- df_long %>% 
  group_by(Gene) %>% 
  mutate(Light_exposure = case_when(sum(grep("i13", paste(variable))) > 0 ~ "yes",
                                    TRUE ~ "no")) %>% ungroup()

df <- structure(list(rsem_outdir_NAi13t3n2_S1 = c(756.624, 0, 357.557, 
1.1, 0, 0), rsem_outdir_NAi13t3n14_S2 = c(906.464, 0, 352.441, 
1.022, 0, 0), rsem_outdir_NAi13t3n26_S3 = c(307.957, 0, 211.422, 
1.04, 0, 0), rsem_outdir_NAi13t3n27_S4 = c(739.13, 0, 268.329, 
1.243, 0, 0), rsem_outdir_NAi13t3n31_S5 = c(206.39, 0, 205.709, 
1.052, 0, 0), rsem_outdir_NAi6t3n1_S6 = c(154.113, 0, 247.21, 
1.458, 0, 0), rsem_outdir_NAi6t3n10_S7 = c(220.125, 0, 346.917, 
0.378, 0, 0), rsem_outdir_NAi6t3n16_S8 = c(554.147, 0, 252.998, 
0.503, 0, 0), rsem_outdir_NAi6t3n24_S9 = c(317.122, 0, 325.901, 
1.32, 0, 0), rsem_outdir_NAi6t3n29_S10 = c(183.428, 0, 216.055, 
1.47, 0, 0), rsem_outdir_NAi13t12n7_S11 = c(125.687, 0, 157.471, 
0.41, 0, 0), rsem_outdir_NAi13t12n10_S12 = c(403.675, 0, 224.673, 
1.034, 0, 0), rsem_outdir_NAi13t12n11_S13 = c(1387.289, 0, 429.794, 
1.657, 0, 0), rsem_outdir_NAi13t12n16_S14 = c(470.699, 0, 145.129, 
0.949, 0, 0), rsem_outdir_NAi13t12n19_S15 = c(401.953, 0, 164.364, 
1.143, 0, 0), rsem_outdir_NAi6t12n3_S16 = c(534.054, 0, 240.231, 
0.814, 0, 0), rsem_outdir_NAi6t12n4_S17 = c(420.981, 0, 204.186, 
0.866, 0, 0), rsem_outdir_NAi6t12n18_S18 = c(509.926, 0, 263.276, 
0.716, 0, 0), rsem_outdir_NAi6t12n23_S19 = c(603.937, 0, 249.055, 
1.038, 0, 0), rsem_outdir_NAi6t12n27_S20 = c(374.14, 0, 293.112, 
1.163, 0, 0)), row.names = c("TRINITY_DN0_c0_g1", "TRINITY_DN0_c13_g1", 
"TRINITY_DN0_c1_g1", "TRINITY_DN0_c1_g2", "TRINITY_DN0_c2_g1", 
"TRINITY_DN0_c40_g1"), class = "data.frame")))


> df

不确定这是否有帮助，但这是

sessionInfo

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] reshape_0.8.9   forcats_0.5.1   stringr_1.5.0   dplyr_1.1.4     purrr_1.0.2    
 [6] readr_2.1.2     tidyr_1.3.0     tibble_3.2.1    ggplot2_3.5.0   tidyverse_1.3.1

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.0 xfun_0.39        haven_2.4.3      colorspace_2.1-0
 [5] vctrs_0.6.5      generics_0.1.3   htmltools_0.5.5  yaml_2.3.7      
 [9] utf8_1.2.3       rlang_1.1.2      pillar_1.9.0     glue_1.6.2      
[13] withr_2.5.0      DBI_1.1.1        dbplyr_2.1.1     modelr_0.1.8    
[17] readxl_1.3.1     plyr_1.8.6       lifecycle_1.0.3  munsell_0.5.0   
[21] gtable_0.3.3     cellranger_1.1.0 rvest_1.0.2      evaluate_0.23   
[25] knitr_1.43       tzdb_0.2.0       fastmap_1.1.1    fansi_1.0.4     
[29] broom_1.0.1      Rcpp_1.0.10      scales_1.3.0     backports_1.3.0 
[33] jsonlite_1.8.8   fs_1.6.1         hms_1.1.1        digest_0.6.33   
[37] stringi_1.7.12   grid_4.1.2       cli_3.6.1        tools_4.1.2     
[41] magrittr_2.0.3   crayon_1.5.2     pkgconfig_2.0.3  ellipsis_0.3.2  
[45] xml2_1.3.3       reprex_2.0.1     lubridate_1.8.0  assertthat_0.2.1
[49] rmarkdown_2.21   httr_1.4.5       rstudioapi_0.13  R6_2.5.1        
[53] compiler_4.1.2  

Answer 1

我怀疑你在找

df |> 
  tibble::rownames_to_column("Gene") |>
  tidyr::pivot_longer(cols = -Gene, 
                      names_to = "Variable", values_to = "Value") |>
  dplyr::mutate(Light_exposure = grepl("i13", Variable))

给予

# A tibble: 120 × 4
   Gene              Variable  Value Light_exposure
   <chr>             <chr>     <dbl> <lgl>         
 1 TRINITY_DN0_c0_g1 rsem_out…  757. TRUE          
 2 TRINITY_DN0_c0_g1 rsem_out…  906. TRUE          
 3 TRINITY_DN0_c0_g1 rsem_out…  308. TRUE          
 4 TRINITY_DN0_c0_g1 rsem_out…  739. TRUE          
 5 TRINITY_DN0_c0_g1 rsem_out…  206. TRUE          
 6 TRINITY_DN0_c0_g1 rsem_out…  154. FALSE         
 7 TRINITY_DN0_c0_g1 rsem_out…  220. FALSE         
 8 TRINITY_DN0_c0_g1 rsem_out…  554. FALSE         
 9 TRINITY_DN0_c0_g1 rsem_out…  317. FALSE         
10 TRINITY_DN0_c0_g1 rsem_out…  183. FALSE         
# ℹ 110 more rows
# ℹ Use `print(n = ...)` to see more rows