R语言 绘图 （ggplot2）

2019-04-15 14:47发布

站内文章 / PIC单片机
16867 0 1301
setwd("C:/Users/yuki_cool/RWorkspace") library(ggplot2) library(gridExtra) ##多张图片组合为一张图片上 library(RColorBrewer) mypalette<-brewer.pal(7,"Reds") paste("aaa","dddd",sep = "") LSQ_data <-read.table("C:/Users/yuki_cool/RWorkspace/JQL_chr_depth_summary.txt",header = TRUE,sep=' ') ### 主题 样式 windowsFonts(A=windowsFont('等线'), B=windowsFont('微软雅黑')) par(family='A') pptblue<-rgb(r=16, g=77, b=96, maxColorValue = 255) pptgrey<-rgb(r=107, g=107, b=107,maxColorValue = 255) pptred<-rgb(r=233, g=77, b=96, maxColorValue = 255) ppttea<-rgb(r=198, g=96, b=52, maxColorValue = 255) pptdark<-rgb(r=69, g=87, b=101, maxColorValue = 255) pptbg<-rgb(r=242, g=242, b=242, maxColorValue = 255) par(bg=pptbg) par(bty='l') par(mar=c(4, 5, 4, 6)) theme<-theme_bw()+theme(legend.position = 'top', #图例位置 text=element_text(face = 'bold'), #字体 panel.background=element_rect(pptbg), #画布背景颜 {MOD} plot.background=element_rect(pptbg), #图形背景颜 {MOD} plot.title = element_text(hjust=0.5,size=16,vjust=0.5), #标题位置 panel.border=element_blank(),#图形边界 panel.grid.major=element_blank(),#element_line(colour='lightgrey',linetype="dashed"), #网格线 panel.grid.minor=element_blank(), #次级网格线 legend.title=element_text(size=20, colour='black', vjust=-0.5,face = "bold"), #图例标题 legend.text=element_text(size=20, colour='black', face = "bold"), #图例文字 legend.background =element_rect(pptbg),#图例背景 axis.text=element_text(size=12,colour="black",family='A'), #坐标轴文字 strip.text=element_text(size=12,colour="red",family='A'),#分面文字 strip.background=element_blank(),#分面的背景 axis.line = element_line(size=0.5, colour = 'black'), #轴颜 {MOD}大小 panel.spacing=unit(30,'mm')) #画布大小 #####chromosome depth summary plot LSQ_dt <- na.omit(data.frame(chrome = LSQ_data$chrome, mean_depth = LSQ_data$chr_depth_sum)) LSQ_plot <- ggplot(LSQ_dt, aes(x = chrome, y = mean_depth))+ geom_bar(stat = "identity", fill=I(mypalette[1])) + plot_theme+ labs( y = "Mean depth") LSQ_plot # # LST_plot <- ggplot(LST_dt, aes(x = chrome, y = mean_depth))+ # geom_bar(stat = "identity")+ plot_theme + # labs( y = "Mean depth") # ggsave(plot = fushengyi_plot, filename = file.path(local_path, "chr_pic.png"), width = 10, height = 6) # #################################### # # # plot <- ggplot(LSQ_data, aes(depth, qc)) +geom_point(aes(color="LSQ")) + # geom_point(data =YZF_data, aes(color="YZF") )+ # geom_point(data =YZJ_data, aes(color="YZJ"))+ # geom_point(data =LST_data, aes(color="LST"))+ # geom_point(data =fushengrong_data, aes(color="FSR"))+ # geom_point(data =fushengyi_data, aes(color="FSY"))+ # labs(color="Sample", x = "sequence depth", y = "Fraction of bases (%)", size = 10) # # # qc_plot <- plot + theme_bw() + plot_theme # # # plot1 <- ggplot(LST_data, aes(depth, ac)) +geom_line(aes(color="LST"),size =1.5) + # geom_line(data =YZJ_data, aes(color="YZJ"),size =1.5)+ # geom_line(data =LSQ_data, aes(color="LSQ"),size =1.5)+ # geom_line(data =YZF_data, aes(color="YZF"),size =1.5)+ # geom_line(data =fushengrong_data, aes(color="FSR"),size =1.5)+ # geom_line(data =fushengyi_data, aes(color="FSY"),size =1.5)+ # labs(color="Sample", x = "cumulative sequence depth", y = "Fraction of bases (%)") # # ac_plot <- plot1+ theme_bw() + plot_theme # # pic<-grid.arrange(qc_plot, ac_plot, ncol = 2) # # # ggsave(plot = ac_plot, filename = file.path(local_path, "ac_pic.png"), width = 10, height = 6)

热门文章