富集分析图左侧名称拥挤解决办法

耐药患者组织与敏感的患者组织内的成纤维细胞比较

-主要修改地方【对比旧代码】

1.theme_bw(base_size = 7)
2.axis.text.y = element_text(size = 7))

library( "ggplot2" )
{
  kegg_down_dt <- as.data.frame( kk.down )
  kegg_up_dt <- as.data.frame( kk.up )
  down_kegg <- kegg_down_dt[ kegg_down_dt$pvalue < 0.05, ]
  down_kegg$group = -1
  up_kegg <- kegg_up_dt[ kegg_up_dt$pvalue < 0.05, ]
  up_kegg$group = 1

  dat = rbind( up_kegg, down_kegg )
  dat$pvalue = -log10( dat$pvalue )
  dat$pvalue = dat$pvalue * dat$group
  
  dat = dat[ order( dat$pvalue, decreasing = F ), ]
  
  g_kegg<- ggplot(dat, aes(x=reorder(Description,order(pvalue, decreasing = F)), y=pvalue, fill=group)) + 
    geom_bar(stat="identity") + 
    scale_fill_gradient(low="blue",high="red",guide = FALSE) + 
    scale_x_discrete(name ="Pathway names") +
    scale_y_continuous(name ="log10P-value") +
    coord_flip() + theme_bw(base_size = 7)+
    theme(plot.title = element_text(hjust = 0.5),  axis.text.y = element_text(size = 7))+
    ggtitle("Pathway Enrichment") 
  
  ###修改了数值，【7，可修改】，下面为旧代码。
  
  # g_kegg <- ggplot( dat, 
  #                   aes(x = reorder( Description, order( pvalue, decreasing=F ) ), y = pvalue, fill = group)) + 
  #   geom_bar( stat = "identity" ) + 
  #   scale_fill_gradient( low = "blue", high = "red", guide = F ) + 
  #   scale_x_discrete( name = "Pathway names" ) +
  #   scale_y_continuous( name = "log10P-value" ) +
  #   coord_flip() + theme_bw() + theme( plot.title = element_text( hjust = 0.5 ) ) +
  #   ggtitle( "Pathway Enrichment" ) 
  print( g_kegg )
  ggsave( g_kegg, filename = 'kegg_up_down.png' )
}