10 Getting List of Nexus Transccription Factors

Robbin Nameki, Anamay Shetty et al. August 2021 # Introduction This section introduces the process of identifying Nexus Transcription Factors. Used for the generation of Supplementary Table 7.

Libraries

library(tidyverse)

Sourcecode

source('Rscripts/Utils.R')

## Warning: package 'valr' was built under R version 4.0.5

Data

This analysis compares MsigDB BROAD GSEA results x the transcription factors on the leading edge of the super-enhancer associated GSEA analysis.

legacy_tf <- getting_legacy_tf_MsigDBGSEA()

histotype = c('HGSOC','LGSOC','CCOC','NMOC','MOC','EnOC')
for(i in histotype) {
  #MAGMA for each histotype
  assign(paste0('MAGMA_sig_',i),
         legacy_tf %>%
           filter(FEATURE == 'MAGMA') %>%
           filter(GWAS_TYPE == paste(i)) %>%
           filter(!is.na(GENE)) %>%
           group_by(FEATURE, GWAS_TYPE) %>%
           filter(NOM.p.val < 0.05) %>%
           filter(FDR.q.val < 0.25)
         ) 
  
  #chromMAGMA for each histotype
  assign(paste0('chromMAGMA_sig_',i),
         legacy_tf %>%
           filter(FEATURE == 'chromMAGMA') %>%
           filter(GWAS_TYPE == paste(i)) %>%
           filter(!is.na(GENE)) %>%
           group_by(FEATURE, GWAS_TYPE) %>%
           filter(NOM.p.val < 0.05) %>%
           filter(FDR.q.val < 0.25)
         )
}

LE_list <- getting_LE_list()
LE_list_nested <- LE_list %>%
  dplyr::rename(GENE = gene_id) %>%
  split(f = as.factor(.$GWAS_TYPE)) 

List

of Nexus TFs (Supplementary Table 7)

#CCOC
chromMAGMA_tf_CCOC <- chromMAGMA_sig_CCOC[chromMAGMA_sig_CCOC$GENE %in% LE_list_nested$clearcell$GENE,]
chromMAGMA_tf_EnOC <- chromMAGMA_sig_EnOC[chromMAGMA_sig_EnOC$GENE %in% LE_list_nested$endometrioid$GENE,]
chromMAGMA_tf_HGSOC <- chromMAGMA_sig_HGSOC[chromMAGMA_sig_HGSOC$GENE %in% LE_list_nested$serous_hg_extra$GENE,]
chromMAGMA_tf_MOC <- chromMAGMA_sig_MOC[chromMAGMA_sig_MOC$GENE %in% LE_list_nested$mucinous_all$GENE,]


LE_list2 <- LE_list %>%
  filter(!GWAS_TYPE == 'mucinous_all') %>%
  dplyr::rename(GENE = gene_id)
chromMAGMA_tf_NMOC <- chromMAGMA_sig_NMOC[chromMAGMA_sig_NMOC$GENE %in% LE_list2$GENE,]

tf_list_final <- rbind(chromMAGMA_tf_CCOC,
      chromMAGMA_tf_EnOC,
      chromMAGMA_tf_HGSOC,
      chromMAGMA_tf_MOC,
      chromMAGMA_tf_NMOC) %>%
  ungroup() %>%
  dplyr::select(MsigdB_NAME,
                GENE,
                GWAS_TYPE)

head(tf_list_final)

## # A tibble: 6 x 3
##   MsigdB_NAME GENE  GWAS_TYPE
##   <chr>       <chr> <chr>    
## 1 EGR1_01     EGR1  CCOC     
## 2 RREB1_01    RREB1 CCOC     
## 3 SP1_Q2_01   SP1   CCOC     
## 4 SP1_Q6      SP1   CCOC     
## 5 SP1_Q4_01   SP1   CCOC     
## 6 SP1_Q6_01   SP1   CCOC

#write.table(x = tf_list_final, file = 'Data/nexus_tfs.6.15.21.txt', append = F, quote = T, sep = '\t', row.names = F, col.names = T)