library(ggplot2)
library(scales)
library(gridExtra)
library(grid)


##################
### BAR COLORS ###
##################

gg_color_hue <- function(n) {
  hues = seq(15, 375, length = n + 1)
  hcl(h = hues, l = 65, c = 100)[1:n]
}
cols = gg_color_hue(6)

uncorrected = cols[1]
hapog_20x   = cols[2]            
hapog_50x   = cols[3] 
hapog_100x  = cols[4] 
hapog_150x  = cols[5] 
hapog_180x  = cols[6] 


#######################
### DATA FORMATTING ###
#######################

dat = read.csv('Arabidopsis_coverage_variation.csv')
dat$Coverage = factor(dat$Coverage, levels=c("Uncorrected", "20x", "50x", "100x", "150x", "180x"))


#####################
### IDENTITY RATE ###
#####################

id_rate_top = ggplot(data=dat, aes(x=Coverage, y=percent_identity)) +
  geom_col(position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none")+
  xlab("") +
  ylab("") +
  scale_y_continuous(breaks=c(0, 99.90, 99.902, 99.904, 99.906, 99.908, 99.91), labels=c("0", "99.900", "99.902", "99.904", "99.906", "99.908", "99.910")) +
  coord_cartesian(ylim=c(99.9, 99.91))

id_rate_bottom = ggplot(data=dat, aes(x=Coverage, y=percent_identity)) +
  geom_col(position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none")+
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("") +
  scale_y_continuous(breaks=c(0, 25, 50, 75, 100), labels=c("0", "25.00", "50.00", "75.00", "100"))

id_rate = grid.arrange(id_rate_top, id_rate_bottom, 
                       heights=c(2, 3), 
                       ncol=1, nrow=2, 
                       left=textGrob("Identity rate(%)", 
                                     rot=90, 
                                     vjust=1))


#####################
### QUALITY SCORE ###
#####################

qscore_top = ggplot(data=dat, aes(x=Coverage, y=Qscore)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("") +
  ylab("") + 
  coord_cartesian(ylim=c(30, 32))

qscore_bottom = ggplot(data=dat, aes(x=Tool, y=Qscore)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("") + 
  scale_y_continuous(breaks=c(0, 10, 20, 30), labels=c("0", "10.0", "20.0", "30.0"))

qscore = grid.arrange(qscore_top, qscore_bottom, 
                      heights=c(2, 3), 
                      ncol=1, nrow=2, 
                      left=textGrob("Quality score", 
                                    rot=90, 
                                    vjust=1))

ggsave("Arabidopsis_qscore.png", plot=qscore, width=16, height=9)


###########################
### 100% identity pairs ### 
###########################

pairs_top = ggplot(data=dat, aes(x=Coverage, y=X100p_pairs)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("") +
  ylab("") + 
  scale_y_continuous(breaks=c(42500000, 43000000, 43500000), labels=c("42.5", "43.0", "43.5")) +
  coord_cartesian(ylim=c(42500000, 43500000))

pairs_bottom = ggplot(data=dat, aes(x=Coverage, y=X100p_pairs)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("") + 
  scale_y_continuous(breaks=c(0, 10000000, 20000000, 30000000, 40000000, 50000000), labels=c("0", "10.0", "20.0", "30.0", "40.0", "50.0"))

pairs = grid.arrange(pairs_top, pairs_bottom, 
                     heights=c(2, 3), 
                     ncol=1, nrow=2, 
                     left=textGrob("Million of perfectly mapped pairs", 
                                   rot=90, 
                                   vjust=1))


#############
### EXONS ###
#############

exons_top = ggplot(data=dat, aes(x=Coverage, y=X100p_exons)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size=12),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("") +
  ylab("") + 
  scale_y_continuous(label=comma, breaks=c(198500, 199000, 199500, 200000)) +
  coord_cartesian(ylim=c(198500, 200000))

exons_bottom = ggplot(data=dat, aes(x=Coverage, y=X100p_exons)) +
  geom_histogram(stat="identity", position=position_dodge2(width = 0.9, preserve = "single"), color="black", fill=c(uncorrected, hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size=12),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("") + 
  scale_y_continuous(label=comma, breaks=c(0, 50000, 100000, 150000, 200000)) +
  coord_cartesian(ylim=c(0, 200000))

exons = grid.arrange(exons_top, exons_bottom, 
                     heights=c(2, 3), 
                     ncol=1, nrow=2, 
                     left=textGrob("Number of exons aligned with 100% identity", 
                                   rot=90, 
                                   vjust=1))


################
### RUN TIME ###
################

dat2 = subset(dat, dat$Tool != "Uncorrected")

run_time = ggplot(data=dat2, aes(x=Coverage, y=run_time)) +
  geom_histogram(stat="identity", position=position_dodge2(preserve = "single"), color="black", fill=c(hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("Total running time (minutes)") +
  #scale_y_continuous(limits=c(0, 210))
  coord_cartesian(ylim=c(0, 50))

id_rate <- arrangeGrob(id_rate, top = textGrob("A", x = unit(0, "npc"),
                                               y   = unit(1, "npc"), just=c("left","top"),
                                               gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))

qscore <- arrangeGrob(qscore, top = textGrob("B", x = unit(0, "npc"),
                                             y = unit(1, "npc"), just=c("left","top"),
                                             gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))

pairs <- arrangeGrob(pairs, top = textGrob("B", x = unit(0, "npc"),
                                           y = unit(1, "npc"), just=c("left","top"),
                                           gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))

exons <- arrangeGrob(exons, top = textGrob("C", x = unit(0, "npc"),
                                           y  = unit(1, "npc"), just=c("left","top"),
                                           gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))

run_time <- arrangeGrob(run_time, top = textGrob("D", x = unit(0, "npc"),
                                                 y = unit(1, "npc"), just=c("left","top"),
                                                 gp=gpar(col="black",    fontsize=18, fontfamily="Times Roman")))

g <- grid.arrange(id_rate, pairs, exons, run_time, ncol=2, nrow=2)
ggsave(file="Arabidopsis_coverage_variation_metrics.png", plot=g, width=16, height=9)


###################
### MEMORY PEAK ###
###################

dat2 = subset(dat, dat$Tool != "Uncorrected")

memory_peak = ggplot(data=dat2, aes(x=Coverage, y=peak_memory.GB.)) +
  geom_histogram(stat="identity", position=position_dodge2(preserve = "single"), color="black", fill=c(hapog_20x, hapog_50x, hapog_100x, hapog_150x, hapog_180x)) +
  theme_bw() +
  theme(axis.text = element_text(size = 14), axis.title = element_text(size = 14),legend.text = element_text(size = 22),plot.title = element_text(size = 22)) +
  theme(legend.position = "none") +
  xlab("Illumina coverage used to polish with Hapo-G") +
  ylab("Memory peak (GB)")+
  scale_y_continuous(limits=c(0, 60))

ggsave(file="Arabidopsis_coverage_variation_memory_peak.png", plot=memory_peak, width=16, height=9)