plot_cnetplot_core.R

library(dplyr)
library(ggplot2)
library(clusterProfiler)
library(org.Hs.eg.db)
    df <- read.csv("./data/core_final_LINCS_ad_gene_nw_modified_with_symbols.csv")  
    top_bottom <- c("top", "bottom")
    universe_genes <- read.csv("./data/universe_genes_LINCS.csv") %>% pull(gene) %>% unique()
    for (name in top_bottom){
        if (name == "top"){
            gene_list <- df %>%
                filter(Weight == 1)%>%
                pull(Target) 
        } else {
            gene_list <- df %>%
                filter(Weight == -1)%>%
                pull(Target) 
        }
        gene_list <- unique(gene_list)
        enrich_results <- enrichGO(
            gene = gene_list,      
            OrgDb = org.Hs.eg.db,            
            keyType = "SYMBOL",
            universe = universe_genes,         
            ont = "BP",
            pAdjustMethod = "BH",                 
            pvalueCutoff = 0.05,        
            qvalueCutoff = 0.05         
        )
        df_result <- as.data.frame(enrich_results)
        write.csv(df_result, file = paste0("./data/core/enr_", name, "_core.csv"), row.names = FALSE)
        
        cnet <- cnetplot(enrich_results,
                       layout = 'circle', 
                       showCategory = 10, 
                       color_edge = "category")
        title <- paste0("Gene-concept network of", name, "10 enriched BPs for core based on ORA")
        cnet <- cnet + ggplot2::ggtitle(title)
        ggplot2::ggsave(paste0("./img/core/cnetplot_", name, "_core.png"), cnet, width = 15, height = 15)
    }