rpotter6298
34 lines
1.4 KiB
R
Executable File
34 lines
1.4 KiB
R
Executable File
msigdb_workflow <- function(signif.genes, category = "C2") {
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library(msigdbr)
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library(ggplot2)
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msigdb_data <- msigdbr(species = "Homo sapiens", category = category)
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# signif.genes <- reports_P03_Transformed_bcrsn$Set_3_limma
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# top_genes <- head(signif.genes[order(signif.genes$adj.P.Val),], 25)
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top_genes <- signif.genes[order(signif.genes$adj.P.Val), ]
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top_genes <- fill_analyte_info(top_genes)
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top_genes <- top_genes$Gene.name
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msigdb_genes <- select(msigdb_data, gs_name, gene_symbol)
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enrich_msigdb <- enricher(top_genes, TERM2GENE = msigdb_genes)
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enrich_msigdb_df <- enrich_msigdb@result %>%
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separate(BgRatio, into = c("size.term", "size.category"), sep = "/") %>%
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separate(GeneRatio, into = c("size.overlap.term", "size.overlap.category"), sep = "/") %>%
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mutate_at(vars("size.term", "size.category", "size.overlap.term", "size.overlap.category"), as.numeric) %>%
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mutate("k.K" = size.overlap.term / size.term)
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enrich_plot <- enrich_msigdb_df %>%
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filter(p.adjust <= 0.05) %>%
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ggplot(aes(x = reorder(Description, k.K), y = k.K)) +
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geom_col() +
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theme_classic() +
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coord_flip() +
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labs(
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y = "Significant genes in set / Total genes in set \nk/K", x = "Gene set",
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title = paste("Differentially expressed genes enriched in", category, "Gene sets (P<0.05)")
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)
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return(list(data = enrich_msigdb_df, plot = enrich_plot))
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}
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