Download the file Bubble_R_allTantigens.csv

library(ggplot2)
library(dplyr)
library(magrittr)
library(tidyr)
library(forcats)

mydat <- read.csv("Bubble_R_allTantigens.csv", sep=";", header=TRUE)
mydat$GeneRatio <- sapply(mydat$GeneRatio_frac, function(x) eval(parse(text=x)))
#mydat$FoldEnrichment <- as.numeric(mydat$FoldEnrichment)
mydat$Regulation <- factor(mydat$Regulation, levels=c("up","down"))
mydat$Comparison <- factor(mydat$Comparison, levels=c("sT vs ctrl d3","sT vs ctrl d8","LT vs ctrl d3","LT vs ctrl d8","LTtr vs ctrl d3","LTtr vs ctrl d8","sT+LT vs ctrl d3","sT+LTtr vs ctrl d912")) 
mydat$Term <- factor(mydat$Term, levels=rev(c("Cell division", "Cell cycle", "Negative regulation of cell proliferation", "Mitotic cell cycle", "Mitotic sister chromatid segregation", "Mitotic spindle organization", "Chromosome segregation", "DNA replication", "DNA repair", "Cellular response to DNA damage stimulus", "Regulation of transcription, DNA-templated", "Positive regulation of transcription, DNA-templated", "Regulation of transcription from RNA polymerase II promoter", "Negative regulation of transcription from RNA polymerase II promoter", "rRNA processing", "Protein folding", "Immune response", "Inflammatory response", "Positive regulation of I-kappaB kinase/NF-kappaB signaling", "Cellular response to tumor necrosis factor", "Chemotaxis", "Neutrophil chemotaxis", "Innate immune response", "Response to virus", "Defense response to virus", "Cellular response to lipopolysaccharide", "Signal transduction", "Response to drug", "Apoptotic process", "Cell adhesion", "Collagen fibril organization", "Nervous system development", "Axon guidance", "Extracellular matrix organization", "Angiogenesis"))) 
tiff("Bubble_all-Tantigens_big.tiff", units = "in", width = 35, height = 50, res=500) 
#png("bubble.png", width=1400, height=600)

xl <- factor(rev(c("Cell division", "Cell cycle", "Negative regulation of cell proliferation", "Mitotic cell cycle", "Mitotic sister chromatid segregation", "Mitotic spindle organization", "Chromosome segregation", "DNA replication", "DNA repair", "Cellular response to DNA damage stimulus", "Regulation of transcription, DNA-templated", "Positive regulation of transcription, DNA-templated", "Regulation of transcription from RNA polymerase II promoter", "Negative regulation of transcription from RNA polymerase II promoter", "rRNA processing", "Protein folding", "Immune response", "Inflammatory response", "Positive regulation of I-kappaB kinase/NF-kappaB signaling", "Cellular response to tumor necrosis factor", "Chemotaxis", "Neutrophil chemotaxis", "Innate immune response", "Response to virus", "Defense response to virus", "Cellular response to lipopolysaccharide", "Signal transduction", "Response to drug", "Apoptotic process", "Cell adhesion", "Collagen fibril organization", "Nervous system development", "Axon guidance", "Extracellular matrix organization", "Angiogenesis")))
bold.terms <- c("Innate immune response", "Response to virus", "Defense response to virus")
bold.labels <- ifelse((xl) %in% bold.terms, yes = "bold", no = "plain")

#-log10(FDR) can be renamed as 'Significance'   
png("bubble_plot.png", 3000, 2000)
ggplot(mydat, aes(y = Term, x = Comparison)) + geom_point(aes(color = Regulation, size = Count, alpha = abs(log10(FDR)))) + scale_color_manual(values = c("up" = "red", "down" = "blue")) + scale_size_continuous(range = c(1, 34)) + labs(x = "", y = "", color="Regulation", size="Count", alpha="-log10(FDR)") + theme(axis.text.y = element_text(face = bold.labels))+ theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) + theme(axis.text = element_text(size = 40)) + theme(legend.text = element_text(size = 40)) + theme(legend.title = element_text(size = 40))+
  guides(color = guide_legend(override.aes = list(size = 20)), alpha = guide_legend(override.aes = list(size = 20)))
dev.off()