Additional file 2: Text S1. Figure and statistics generation script.

# Load packages

library(ggplot2)
library(gridExtra)
library(ggpubr)
library(scales)
library(pastecs)

# The working directory should be set to where you have the bioassay_data.csv file is located
# use setwd("path/to/dir/with/data")

dat <- read.csv("bioassay_data.csv")
dat$type <- as.factor(dat$type)

dat_k = dat[dat$strain == 'Kilifi', ]
dat_k[dat_k$mortality_24 < 75,]

dat_m = dat[dat$strain == 'Mbita', ]

dat$type <- as.factor(dat$type)
kil_plot <- ggplot(dat_k, aes(x=type, y=mortality_24)) + geom_boxplot(fill='skyblue', outlier.shape = NA)
#kil_plot <- kil_plot + geom_point(aes(), size = 4, shape = 4)
kil_plot <- kil_plot + coord_cartesian(ylim = c(75, 100))
kil_plot <- kil_plot + xlab(" ") + ylab(" ") + ggtitle('Kilifi') + theme(plot.title = element_text(hjust = 0.5))
kil_plot <- kil_plot + stat_compare_means(method = "t.test",
                                          label.x = 1.2, label.y = 100.5) + theme(plot.margin=grid::unit(c(0,0,0,0), "mm"))

kil_plot

mbi_plot <- ggplot(dat_m, aes(x=type, y=mortality_24)) + geom_boxplot(fill='skyblue', outlier.shape = NA)
#mbi_plot <- mbi_plot + geom_point(aes(), size = 4, shape = 4)
mbi_plot <- mbi_plot + coord_cartesian(ylim = c(75, 100))
mbi_plot <- mbi_plot + xlab(" ") + ylab("24hr Mortality (%)") + ggtitle('Mbita') + theme(plot.title = element_text(hjust = 0.5))
mbi_plot <- mbi_plot + stat_compare_means(method = "t.test",
                                          label.x = 1.2, label.y = 100.5) + theme(plot.margin=grid::unit(c(0,0,0,0), "mm"))

mbi_plot


combined_plot <- ggplot(dat, aes(x=type, y=mortality_24)) + geom_boxplot(fill='skyblue', outlier.shape = NA)
#mbi_plot <- mbi_plot + geom_point(aes(), size = 4, shape = 4)
combined_plot <- combined_plot + coord_cartesian(ylim = c(75, 100))
combined_plot <- combined_plot + xlab(" ") + ylab(" ") + ggtitle('Combined') + theme(plot.title = element_text(hjust = 0.5))
combined_plot <- combined_plot + stat_compare_means(method = "t.test",
                                                    label.x = 1.2, label.y = 100.5) + theme(plot.margin=grid::unit(c(0,0,0,0), "mm"))

combined_plot

blank_theme <- theme_minimal()+
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    panel.border = element_blank(),
    panel.grid=element_blank(),
    axis.ticks = element_blank(),
    plot.title=element_text(size=14, face="bold"),
    plot.margin=grid::unit(c(0,0,0,0), "mm")
  )
# Save bar plots
plot <- ggarrange(mbi_plot, kil_plot, combined_plot, ncol=3)
plot

ggsave("Figure_3.png", plot=plot, width = 6, height = 8)


# Summary Statsitics

stat.desc(dat[dat$type=='3D' & dat$strain == 'Mbita',]$mortality_24)
stat.desc(dat[dat$type=='3D' & dat$strain == 'Kilifi',]$mortality_24)
stat.desc(dat[dat$type=='WHO' & dat$strain == 'Mbita',]$mortality_24)
stat.desc(dat[dat$type=='WHO' & dat$strain == 'Kilifi',]$mortality_24)

# Count n
nrow(dat[dat$type=='3D' & dat$strain == 'Mbita',])
nrow(dat[dat$type=='3D' & dat$strain == 'Kilifi',])
nrow(dat[dat$type=='WHO' & dat$strain == 'Mbita',])
nrow(dat[dat$type=='WHO' & dat$strain == 'Kilifi',])