fig a

library(dplyr)
library(viridis)
library(hrbrthemes)
library(ggplot2)
library(reshape2)

data <- read.csv("arab_500sra_intron_10sample.csv", header = TRUE,sep=',',encoding="utf-8")
data$percent=data$percent*10
pic=ggplot(data,aes(x=percent,y=GC))+
	stat_summary(fun.data="mean_cl_boot",geom="ribbon",alpha=I(.5),fill="#8FD1F1")+
	stat_summary(fun="mean",geom="line",size=1.5,linetype=2, color="#269FCC")+
	labs(x="Percent", y="GC") +
	coord_cartesian(ylim = c(0.315,0.335))+
	theme_bw()+
	theme(axis.title.x= element_text(size=40),
		axis.title.y= element_text(size=40),
		axis.text.x = element_text( size=40),
		axis.text.y = element_text(size=40),
		panel.grid.minor.x=element_blank(),
		panel.grid.minor.y=element_blank())

jpeg(file="fig_a.jpg", width=10, height=9, units="in", res=500)
pic
dev.off()

fig b

library(dplyr)
library(viridis)
library(hrbrthemes)
library(ggplot2)
library(reshape2)

data <- read.csv("rice_500sra_intron_10sample.csv", header = TRUE,sep=',',encoding="utf-8")
data$percent=data$percent*10
pic=ggplot(data,aes(x=percent,y=GC))+
	stat_summary(fun.data="mean_cl_boot",geom="ribbon",alpha=I(.5),fill="#8FD1F1")+
	stat_summary(fun="mean",geom="line",size=1.5,linetype=2, color="#269FCC")+
	labs(x="Percent", y="GC") +
	coord_cartesian(ylim = c(0.36,0.39))+
	theme_bw()+
	theme(axis.title.x= element_text(size=40),
		axis.title.y= element_text(size=40),
		axis.text.x = element_text( size=40),
		axis.text.y = element_text(size=40),
		panel.grid.minor.x=element_blank(),
		panel.grid.minor.y=element_blank())

jpeg(file="fig_b.jpg", width=10, height=9, units="in", res=500)
pic
dev.off()