PlottingScripts/figure3-plot.R
In eLifeProduction/hrp2malaRia_2019: pfhrp2 gene deletion malaria modelling
# figure 3 plot
# ------------------------------------------------------------------
# load packages
require(ggplot2)
require(Rmisc)
require(ggplot2)
require(grid)
require(gridExtra)
require(viridis)
# Extra functions
# ------------------------------------------------------------------
fmt_dcimals <- function(decimals=0){
function(x) format(x,nsmall = decimals,scientific = FALSE)
}
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
# ------------------------------------------------------------------
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c("NULL","character",rep("numeric",7),rep("NULL",8)))
fig3a_simulated <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c(rep("NULL",10),rep("numeric",2),"character",rep("NULL",4)))
colnames(fig3a_simulated)[3] <- "Province"
df <- as.data.frame(list("Prevalence"=fig3a_simulated$PCR.PfPR.6.59.months,
"Dels"=fig3a_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=fig3a_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
##
# ------------------------------------------------------------------
fig3a <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.7)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.7,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c("NULL","character",rep("numeric",7),rep("NULL",8)))
fig3b_simulated <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c(rep("NULL",14),rep("numeric",2),"character"))
colnames(fig3b_simulated)[3] <- "Province"
df <- as.data.frame(list("Prevalence"=fig3b_simulated$PCR.PfPR.6.59.months,
"Dels"=fig3b_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=fig3b_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
##
# ------------------------------------------------------------------
fig3b <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.7)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.7,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
## PLOTTING
# ------------------------------------------------------------------
g1 <- ggplotGrob(fig3a)
g2 <- ggplotGrob(fig3b)
g2$widths <- g1$widths
myplot1 <- arrangeGrob(g1, top = textGrob("a", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
myplot2 <- arrangeGrob(g2, top = textGrob("b", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
windows()
gridExtra::grid.arrange(myplot1,myplot2,ncol=1)
# figure 3 - supplement figure 1 plot
# ------------------------------------------------------------------
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"))
figs3_s1_simulated <- read.csv(system.file("extdata","fig3_s1.csv",package="hrp2malaRia"))
df <- as.data.frame(list("Prevalence"=figs3_s1_simulated$PCR.PfPR.6.59.months,
"Dels"=figs3_s1_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=figs3_s1_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
dfcomps <- as.data.frame(list("DHS" = fig3_observed$propDel,"Simulation" = dfmean$Dels,"Province"=fig3_observed$Province,
"Diff" = abs(fig3_observed$propDel-dfmean$Dels)))
fig3_s1a <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.6)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.6,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
fig3_s1b <- ggplot(dfcomps, aes(x=DHS,y=Simulation))+
#ggtitle("Simulation vs DHS") +
theme_classic() + theme_light() + theme_linedraw() +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(2),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.7, nudge_y = -1,nudge_x = -0.3) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(3),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.7, nudge_y = -1,nudge_x = -0.3) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(1),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.5, nudge_y = -1) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(4),],aes(x=DHS,y=Simulation,label=Province),hjust = 1, nudge_y = -0,nudge_x = -0.5) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(5),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.2, nudge_y = -0) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(6),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.2, nudge_y = -0) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(7),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.1, nudge_y = -0.4) +
geom_segment(aes(x = DHS, y = Simulation,xend = DHS, yend = DHS),colour="grey") +
geom_abline(slope=1) +
geom_point(colour="red") +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
## PLOTTING
# ------------------------------------------------------------------
g1 <- ggplotGrob(fig3_s1a)
g2 <- ggplotGrob(fig3_s1b)
g2$widths <- g1$widths
myplot1 <- arrangeGrob(g1, top = textGrob("a", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
myplot2 <- arrangeGrob(g2, top = textGrob("b", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
windows()
gridExtra::grid.arrange(myplot1,myplot2,ncol=1)
eLifeProduction/hrp2malaRia_2019 documentation built on May 9, 2019, 12:04 a.m.
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# figure 3 plot
# ------------------------------------------------------------------
# load packages
require(ggplot2)
require(Rmisc)
require(ggplot2)
require(grid)
require(gridExtra)
require(viridis)
# Extra functions
# ------------------------------------------------------------------
fmt_dcimals <- function(decimals=0){
function(x) format(x,nsmall = decimals,scientific = FALSE)
}
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
# ------------------------------------------------------------------
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c("NULL","character",rep("numeric",7),rep("NULL",8)))
fig3a_simulated <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c(rep("NULL",10),rep("numeric",2),"character",rep("NULL",4)))
colnames(fig3a_simulated)[3] <- "Province"
df <- as.data.frame(list("Prevalence"=fig3a_simulated$PCR.PfPR.6.59.months,
"Dels"=fig3a_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=fig3a_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
##
# ------------------------------------------------------------------
fig3a <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.7)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.7,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c("NULL","character",rep("numeric",7),rep("NULL",8)))
fig3b_simulated <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"),colClasses = c(rep("NULL",14),rep("numeric",2),"character"))
colnames(fig3b_simulated)[3] <- "Province"
df <- as.data.frame(list("Prevalence"=fig3b_simulated$PCR.PfPR.6.59.months,
"Dels"=fig3b_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=fig3b_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
##
# ------------------------------------------------------------------
fig3b <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.7)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.7,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
## PLOTTING
# ------------------------------------------------------------------
g1 <- ggplotGrob(fig3a)
g2 <- ggplotGrob(fig3b)
g2$widths <- g1$widths
myplot1 <- arrangeGrob(g1, top = textGrob("a", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
myplot2 <- arrangeGrob(g2, top = textGrob("b", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
windows()
gridExtra::grid.arrange(myplot1,myplot2,ncol=1)
# figure 3 - supplement figure 1 plot
# ------------------------------------------------------------------
# Read in observed source data - This is the observed data of hrp2 deletions collected by Parr at al 2016 (Pfhrp2-deleted Plasmodium falciparum parasites in the Democratic Republic of Congo: A national cross-sectional survey. J Infect Dis: 1–34. doi:10.1093/ecco-jcc/jjw024),
fig3_observed <- read.csv(system.file("extdata","fig3.csv",package="hrp2malaRia"))
figs3_s1_simulated <- read.csv(system.file("extdata","fig3_s1.csv",package="hrp2malaRia"))
df <- as.data.frame(list("Prevalence"=figs3_s1_simulated$PCR.PfPR.6.59.months,
"Dels"=figs3_s1_simulated$Proportion.Population.only.infected.with.pfhrp2.deleted.mutants,
"Province"=figs3_s1_simulated$Province))
dfmean <- as.data.frame(list("Prevalence"=colMeans(matrix(df$Prevalence,nrow=10,byrow=T)),
"Dels"=colMeans(matrix(df$Dels,nrow=10,byrow=T)),
"Dels_U95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Dels_L95"=apply((matrix(df$Dels,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Prevalence_U95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[1,],
"Prevalence_L95"=apply((matrix(df$Prevalence,nrow=10,byrow=T)),2,Rmisc::CI)[3,],
"Province"=rep(df$Province,1)))
dfcomps <- as.data.frame(list("DHS" = fig3_observed$propDel,"Simulation" = dfmean$Dels,"Province"=fig3_observed$Province,
"Diff" = abs(fig3_observed$propDel-dfmean$Dels)))
fig3_s1a <- ggplot(data = fig3_observed,aes(x=PCR.05,y=propDel,label=Province)) +
geom_point(colour="black",alpha=.33) +
geom_line(data=data.frame(loess.smooth(fig3_observed$PCR.05,fig3_observed$propDel,span =0.6)),aes(x=x,y=y,colour="y"),inherit.aes = F) +
geom_errorbar(data = fig3_observed, aes(x = PCR.05, y = propDel, ymin = propDel.L95, ymax = propDel.U95),
colour = 'grey', width = 0.4,alpha=0.66,size=0.25) +
geom_errorbarh(data = fig3_observed, aes(x = PCR.05, y = propDel, xmin = PCR.05.L95, xmax = PCR.05.U95),
colour = 'grey',alpha=0.66,size=0.25) +
geom_point(data = dfmean, aes(x=Prevalence,y = Dels,colour="Dels"),inherit.aes = F,alpha=0.8) +
geom_smooth(data = df,aes(x=Prevalence,y = Dels),inherit.aes = F,se=F,span=0.6,method = "loess",colour="red",alpha=0.75,size=0.5) +
xlab("PCR PfPR 6-59 months") + ylab(expression(paste("Proportion infected with only ",italic(pfhrp2),"-deleted mutants"))) +
scale_colour_manual("",breaks = c("y", "Dels"),values = c("y"="black", "Dels"="red"),labels=c("DHS Dataset","Simulation")) +
geom_errorbar(data = dfmean, aes(x = Prevalence, y = Dels, ymin = Dels_L95, ymax = Dels_U95),colour = 'red', width = 0.4,size=0.25) +
geom_errorbarh(data = dfmean, aes(x = Prevalence, y = Dels, xmin = Prevalence_L95, xmax = Prevalence_U95),colour = 'red',size=0.25) +
#geom_vline(xintercept = DRC_Dels$Updated.PCR.05,linetype="dashed",color="grey",alpha=0.5) +
theme_classic() + theme_light() + theme_linedraw() +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
fig3_s1b <- ggplot(dfcomps, aes(x=DHS,y=Simulation))+
#ggtitle("Simulation vs DHS") +
theme_classic() + theme_light() + theme_linedraw() +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(2),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.7, nudge_y = -1,nudge_x = -0.3) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(3),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.7, nudge_y = -1,nudge_x = -0.3) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(1),],aes(x=DHS,y=Simulation,label=Province),hjust = 0.5, nudge_y = -1) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(4),],aes(x=DHS,y=Simulation,label=Province),hjust = 1, nudge_y = -0,nudge_x = -0.5) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(5),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.2, nudge_y = -0) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(6),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.2, nudge_y = -0) +
geom_text(data = dfcomps[dfcomps$Diff>5,][c(7),],aes(x=DHS,y=Simulation,label=Province),hjust = -0.1, nudge_y = -0.4) +
geom_segment(aes(x = DHS, y = Simulation,xend = DHS, yend = DHS),colour="grey") +
geom_abline(slope=1) +
geom_point(colour="red") +
theme(axis.title.x = element_text(margin=margin(10)), axis.title.y = element_text(margin=margin(c(0,10))),
text=element_text(size=10, family="Times New Roman"),plot.title=element_text(size=12,family="Times New Roman"),
panel.grid.major.x = element_blank(),panel.grid.minor.x = element_blank(),panel.grid.major.y = element_blank(),panel.grid.minor.y = element_blank())
## PLOTTING
# ------------------------------------------------------------------
g1 <- ggplotGrob(fig3_s1a)
g2 <- ggplotGrob(fig3_s1b)
g2$widths <- g1$widths
myplot1 <- arrangeGrob(g1, top = textGrob("a", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
myplot2 <- arrangeGrob(g2, top = textGrob("b", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times New Roman")))
windows()
gridExtra::grid.arrange(myplot1,myplot2,ncol=1)
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