In adamsardar/metaDEGth: Combining differential expression P-values in a statistically consistent fashion whilst respecting background signal/noise trends

TTRUST is a manually created database of human and mouse transcriptional regulation. The human dataset will serve as a perfect example transcription factor - target relations. Further, they are availab

library(data.table)
library(rvest)

TTRUST <- fread("https://www.grnpedia.org/trrust/data/trrust_rawdata.human.tsv",
                col.names = c("TF","target","modulation","PubMedID"))

TTRUSThumanSymbolMap <- html("https://www.grnpedia.org/trrust/data/search_list.human.htm") %>% html_table() %>% .[[1]]

setDT(TTRUSThumanSymbolMap, check.names = TRUE)

TTRUST comes with gene symbols, which are little to no good in deep omics work. We shall use their values to map to gene IDs and then the uniprot ID mapping file to annoate

ENST2ENSG <- fread('zcat /tmp/Homo_sapiens.GRCh38.cdna.all.fa.gz | grep "^>" | perl -pe "s/(>|chromosome:|gene:|GRCh38:|gene_biotype:|transcript_biotype:|gene_symbol:)//g" | perl -ne "s/\\s+/\\t/g; CORE::say $_" | cut -f1-7 ' , header = FALSE, fill = TRUE)

colnames(ENST2ENSG) <- c("ENST","havanaStatus","chromosome","ENSG","geneStatus","geneStatus","geneSymbol")

geneSymbols2map <- unique(c(TTRUST$TF, TTRUST$target))

geneSymbols2ENSG <- ENST2ENSG %>% 
  .[geneStatus == "protein_coding"] %>%
  .[geneSymbol %in% geneSymbols2map, .(ENSG = str_remove_all(ENSG, "\\.\\d+$"), geneStatus, geneSymbol)] %>% 
  unique

TTRUST[TTRUSThumanSymbolMap, geneID := Entrez.ID, on = .(target==Gene.symbol)]

TTRUST %<>% merge(
      geneSymbols2ENSG[,.(geneSymbol, ENSG)],
      by.x = "target",
      by.y = "geneSymbol",
      all.x = TRUE)

TTRUST[is.na(ENSG)] 

A handful of entries do not map. Should be fit for purpose

TTRUST_TF2targets_DT <- TTRUST

save(TTRUST_TF2targets_DT, file = "./data/TTRUST_TF2targets_DT.RData", compress = "xz")

adamsardar/metaDEGth documentation built on Sept. 28, 2022, 10:12 p.m.