KEGG富集分析结果可视化

library(ggplot2)
library(ggthemes)
tab<-read.table("leaf.ori.IDs.keggEnrich.tab.final.xls",header=T,sep="\t")
colnames(tab)
tab<-tab[,c("Term.Name","MainClass",
                                           "GeneHitsInSelectedSet",
                                           "GeneHitsInBackground"
                                           )]
head(tab)
tab$richFactor<-tab$GeneHitsInSelectedSet/tab$GeneHitsInBackground

tab<-tab[order(tab$richFactor,decreasing = T),]
tab<-tab[order(tab$MainClass,decreasing = F),]

tab$Term.Name<-factor(tab$Term.Name,levels=unique(as.character(tab$Term.Name)))
p<-ggplot(tab,aes(x=Term.Name,y=richFactor))
p+geom_bar(stat="identity",width=0.1)+geom_point(aes(color=MainClass),size=10)+
  geom_text(aes(label=GeneHitsInSelectedSet),alpha=I(0.8))+
  theme_bw() +
  theme(
    
    panel.border = element_blank(),
    panel.background = element_blank(),
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(), # element_line(size = 0.8,color="darkgray"), # element_blank(),
    axis.line.x = element_line(colour = "black", size = 0.8),
    axis.line.y = element_line(colour = "black", size = 0.8),
    axis.ticks.x = element_line(size = 0.8),
    axis.ticks.y = element_line(size = 0.8),
    axis.text.x = element_text(
      angle = 90, hjust = 0, vjust = 0
    ),
   #  legend.position="NA",
    legend.key = element_blank(),
    legend.title = element_blank(),
    legend.text = element_text(size = 12, face = "bold"),
    legend.background = element_rect(fill = "transparent"),
    strip.background = element_rect(
      colour = "white", fill = "white",
      size = 0.2
    ),
    strip.text.x = element_text(size = 14),
    strip.text.y = element_text(size = 14),
    
    text = element_text(
      size = 14, 
      #family = "arial",
      face = "bold"
    ),
    plot.title = element_text(
      size = 16, 
      #family = "arial",
      face = "bold"
    )
  )+scale_color_pander()+xlab("KEGG Pathway")+ylab("Rich Factor")