Created
December 19, 2024 13:00
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Get REACTOME terms and associated genes independent of the REACTOME website via ReactomePA
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| library(tidyverse) | |
| library(ReactomePA) | |
| library(biomaRt) | |
| r_human <- ReactomePA:::get_Reactome_DATA("human") | |
| # This package maps to Entrez so we need the conversion table to Ensembl IDs | |
| human_entrez2ensembl <- getBM( | |
| attributes = c("entrezgene_id", "ensembl_gene_id"), | |
| mart = mart_human | |
| ) %>% | |
| setNames(c("entrez_id", "gene_id")) %>% | |
| mutate(entrez_id = as.character(entrez_id)) | |
| # Named list with names being pathway IDs and elements being Entrez genes | |
| reac2entrez <- tibble::enframe(r_human$PATHID2EXTID, name = "reactome_id", value = "entrez_id") %>% unnest("entrez_id") | |
| reac2name <- data.frame(reactome_id = names(r_human$PATHID2NAME), pathway = as.character(r_human$PATHID2NAME)) | |
| # Merge with Ensembl ID | |
| human_reactome <- | |
| inner_join(x = human_entrez2ensembl, y = reac2entrez, by = "entrez_id", relationship = "many-to-many") %>% | |
| inner_join(x = ., y = genes_human, by = "gene_id", relationship = "many-to-many") %>% | |
| mutate(gene = paste(gene_id, gene_name, sep = "_")) %>% | |
| inner_join(x = ., y = reac2name, by = "reactome_id") %>% | |
| dplyr::select(pathway, gene) %>% | |
| arrange(pathway) %>% | |
| unique() |
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