Transcription factor effects from RegNetwork
Examples
regn_dir <- regnetwork_directions()
regn_dir
#> # A tibble: 3,954 × 5
#> source_genesymbol source_entrez target_genesymbol target_entrez effect
#> <chr> <chr> <chr> <chr> <dbl>
#> 1 AHR 196 CDKN1B 1027 1
#> 2 APLNR 187 PIK3C3 5289 1
#> 3 APLNR 187 PIK3R4 30849 1
#> 4 AR 367 KLK3 354 1
#> 5 ARNT 405 ALDOA 226 1
#> 6 ARNT 405 ANGPT1 284 1
#> 7 ARNT 405 ANGPT2 285 1
#> 8 ARNT 405 ANGPT4 51378 1
#> 9 ARNT 405 BCL2 596 1
#> 10 ARNT 405 CDKN1A 1026 1
#> # ℹ 3,944 more rows
# # A tibble: 3,954 x 5
# source_genesymb. source_entrez target_genesymb. target_entrez
# <chr> <chr> <chr> <chr>
# 1 AHR 196 CDKN1B 1027
# 2 APLNR 187 PIK3C3 5289
# 3 APLNR 187 PIK3R4 30849
# 4 AR 367 KLK3 354
# 5 ARNT 405 ALDOA 226
# # . with 3,944 more rows, and 1 more variable: effect <dbl>