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hist_term_GO.R

+library(dplyr)
+library(ggplot2)
+library(forcats)
+
+# input file
+WEGO <- read.table("data/pantherdb/go.tsv", header = FALSE, sep = ";")
+colnames(WEGO) <- c("ID", "Domain","factor", "Number of genes", "Percentage of genes", "raw P_value", "FDR", "Description")
+
+categories <- WEGO %>%
+    group_by(factor) %>% 
+    top_n(5, `Percentage of genes`) %>%
+    .$ID 
+
+WEGO2 <- filter(WEGO, ID %in% categories) %>%
+    arrange(factor, `Percentage of genes`) %>% 
+    mutate(Position = n():1)  
+
+normalizer <- max(WEGO2$`Number of genes`)/max(WEGO2$`Percentage of genes`)
+
+#plot
+p3 <- ggplot(data = WEGO2, aes(x = fct_reorder(Description, Position), y = -log10(FDR), fill = factor)) +
+    geom_col() +
+    scale_fill_manual(values=c("indianred1", "indianred4","deepskyblue1", "deepskyblue4")) +
+    theme(axis.text.x = element_text(hjust = 1), axis.title.y = element_text(size = 8),
+         legend.text = element_text(size = 7), legend.title = element_text(size = 8),
+         legend.key.size =  unit(0.2, "in"), plot.title = element_text(size = 11, hjust = 0.5),
+         panel.background = element_blank(), 
+         axis.line = element_line(colour = "grey")) +
+    coord_flip() +
+    labs(x = NULL, title = "Gene Ontology (GO) Annotation")
+
+ggsave("plots/geneOnto.png", p3, height = 5, width = 8)
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