3 args <- commandArgs(trailingOnly = TRUE)
8 #pdf(file=output,height=6.18,width=10)
10 raw.tab <- read.table(file=input,sep ="\t",header = T)
11 input.tab <- subset(raw.tab, select = -1 )
12 name <- names(input.tab)
15 for (i in 1:ncol(input.tab)){
16 # input.tab[is.na(input.tab)] <- -1
17 invalues <- log10(input.tab[,i])
18 # invalues <- input.tab[,i]
20 ggplot(data=input.tab,aes(x=invalues)) +
21 geom_histogram(position="dodge", bins = 200,na.rm = TRUE, color="darkblue", fill="lightblue") +
22 labs(title=name[i],x="log10(Depth)",y="Number of SNP",size=20) +
24 # theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank()) +
25 theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank(), axis.line = element_line(colour = "black")) +
26 scale_y_continuous(breaks=seq(0,10000,100)) +
27 theme(axis.title.x = element_text(size = 10, color = "black", face = "italic", vjust = 0.5, hjust = 0.5)) +
28 theme(axis.title.y = element_text(size = 10, color = "black", face = "italic", vjust = 0.5, hjust = 0.5)) +
29 theme(axis.text.x = element_text(size = 8, color = "black", face = "bold", vjust = 0.5, hjust = 0.5)) +
30 theme(axis.text.y = element_text(size = 8, color = "black", face = "bold", vjust = 0.5, hjust = 0.5)) +
31 theme(legend.text = element_text(size = 8, color = "black", face = "bold", vjust = 0.5, hjust = 0.5))