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surv_figures.R
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surv_figures.R
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#script for survival curves with log-rank p values aired with distribution curves with ks p values
### load libraries ----
if (!require('survival')) install.packages('survival')
library(survival) #for generating survival curves
if (!require('survminer')) install.packages('survminer')
library(survminer) #for generating customized surviva plots
if (!require('patchwork')) install.packages('patchwork')
library(patchwork) #for putting plots together
#function to swap a few data sets when needed
swap <- function(vec, from, to) {
tmp <- to[ match(vec, from) ]
tmp[is.na(tmp)] <- vec[is.na(tmp)]
return(tmp)
}
## blca w cisplatin 47 ----
blca_cisplatin_surv_df <- read.table('Survival_Data/blca_cisplatin_surv.df.txt', header = TRUE)
#fit survival curves
blca_cisplatin_fit <- survfit(Surv(blca_surv_times, blca_status) ~ X1,
data = blca_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(blca_cisplatin_fit, data = blca_cisplatin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 2500, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
blca_cisplatin_ks_test <- ks.test(blca_cisplatin_surv_df$blca_surv_times[blca_cisplatin_surv_df$X1 == 1],
blca_cisplatin_surv_df$blca_surv_times[blca_cisplatin_surv_df$X1 == 0])
blca_cisplatin_ks_test_p_value <- round(blca_cisplatin_ks_test$p.value, digits = 6)
#density plot
dens_plot <- ggplot(blca_cisplatin_surv_df, aes(x = blca_cisplatin_surv_df$blca_surv_times, fill = factor(blca_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 3500, y = 0.0013,
label = paste0('KS\np = ', blca_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/blca_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## cesc w cisplatin 100 ----
cesc_cisplatin_surv_df <- read.table('Survival_Data/cesc_cisplatin_surv.df.txt', header = TRUE)
#fit survival curves
cesc_cisplatin_fit <- survfit(Surv(cesc_surv_times, cesc_status) ~ X1,
data = cesc_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(cesc_cisplatin_fit, data = cesc_cisplatin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 2500, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
cesc_cisplatin_ks_test <- ks.test(cesc_cisplatin_surv_df$cesc_surv_times[cesc_cisplatin_surv_df$X1 == 1],
cesc_cisplatin_surv_df$cesc_surv_times[cesc_cisplatin_surv_df$X1 == 0])
cesc_cisplatin_ks_test_p_value <- round(cesc_cisplatin_ks_test$p.value, digits = 3)
#density plot
dens_plot <- ggplot(cesc_cisplatin_surv_df, aes(x = cesc_cisplatin_surv_df$cesc_surv_times, fill = factor(cesc_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 3500, y = 7.5e-4,
label = paste0('KS\np = ', cesc_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/cesc_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## esca w cisplatin 10 ----
esca_cisplatin_surv_df <- read.table('Survival_Data/esca_cisplatin_surv_df.txt', header = TRUE)
esca_cisplatin_surv_df$X1 <- swap(esca_cisplatin_surv_df$X1, c(0, 1), c(1, 0))
#fit survival curves
esca_cisplatin_fit <- survfit(Surv(esca_surv_times, esca_status) ~ X1,
data = esca_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(esca_cisplatin_fit, data = esca_cisplatin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 1*365, linetype = 'dashed') +
annotate('text', x = 500, y = 0.25,
label = '1-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
esca_cisplatin_ks_test <- ks.test(esca_cisplatin_surv_df$esca_surv_times[esca_cisplatin_surv_df$X1 == 1],
esca_cisplatin_surv_df$esca_surv_times[esca_cisplatin_surv_df$X1 == 0])
esca_cisplatin_ks_test_p_value <- round(esca_cisplatin_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(esca_cisplatin_surv_df, aes(x = esca_cisplatin_surv_df$esca_surv_times, fill = factor(esca_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 750, y = 0.015,
label = paste0('KS\np = ', esca_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/esca_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## hnsc w cisplatin 65 ----
hnsc_cisplatin_surv_df <- read.table('Survival_Data/hnsc_cisplatin_surv_df.txt', header = TRUE)
#fit survival curves
hnsc_cisplatin_fit <- survfit(Surv(hnsc_surv_times, hnsc_status) ~ X1,
data = hnsc_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(hnsc_cisplatin_fit, data = hnsc_cisplatin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 2300, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
hnsc_cisplatin_ks_test <- ks.test(hnsc_cisplatin_surv_df$hnsc_surv_times[hnsc_cisplatin_surv_df$X1 == 1],
hnsc_cisplatin_surv_df$hnsc_surv_times[hnsc_cisplatin_surv_df$X1 == 0])
hnsc_cisplatin_ks_test_p_value <- round(hnsc_cisplatin_ks_test$p.value, digits = 3)
#density plot
dens_plot <- ggplot(hnsc_cisplatin_surv_df, aes(x = hnsc_cisplatin_surv_df$hnsc_surv_times, fill = factor(hnsc_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 2000, y = 0.0008,
label = paste0('KS\np = ', hnsc_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/hnsc_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## luad w cisplatin 23 ----
luad_cisplatin_surv_df <- read.table('Survival_Data/luad_cisplatin_surv_df.txt', header = TRUE)
#fit survival curves
luad_cisplatin_fit <- survfit(Surv(luad_surv_times, luad_status) ~ X1,
data = luad_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(luad_cisplatin_fit, data = luad_cisplatin_surv_df,
size = 1, #change line size
palette = c('purple', 'limegreen'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Resistant', 'Sensitive'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 2300, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
luad_cisplatin_ks_test <- ks.test(luad_cisplatin_surv_df$luad_surv_times[luad_cisplatin_surv_df$X1 == 1],
luad_cisplatin_surv_df$luad_surv_times[luad_cisplatin_surv_df$X1 == 0])
luad_cisplatin_ks_test_p_value <- round(luad_cisplatin_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(luad_cisplatin_surv_df, aes(x = luad_cisplatin_surv_df$luad_surv_times, fill = factor(luad_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('purple', 'limegreen'), labels = c('Resistant', 'Sensitive')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 2000, y = 0.0012,
label = paste0('KS\np = ', luad_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/luad_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## ov w cisplatin 17 ----
ov_cisplatin_surv_df <- read.table('Survival_Data/ov_cisplatin_surv_df.txt', header = TRUE)
#fit survival curves
ov_cisplatin_fit <- survfit(Surv(ov_surv_times, ov_status) ~ X1,
data = ov_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(ov_cisplatin_fit, data = ov_cisplatin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 1500, y = 0.85,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
ov_cisplatin_ks_test <- ks.test(ov_cisplatin_surv_df$ov_surv_times[ov_cisplatin_surv_df$X1 == 1],
ov_cisplatin_surv_df$ov_surv_times[ov_cisplatin_surv_df$X1 == 2])
ov_cisplatin_ks_test_p_value <- round(ov_cisplatin_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(ov_cisplatin_surv_df, aes(x = ov_cisplatin_surv_df$ov_surv_times, fill = factor(ov_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 1300, y = 0.0008,
label = paste0('KS\np = ', ov_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/ov_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## tgct w cisplatin 48 ----
tgct_cisplatin_surv_df <- read.table('Survival_Data/tgct_cisplatin_surv_df.txt', header = TRUE)
#fit survival curves
tgct_cisplatin_fit <- survfit(Surv(tgct_surv_times, tgct_status) ~ X1,
data = tgct_cisplatin_surv_df)
#plot them
surv_plot <- ggsurvplot(tgct_cisplatin_fit, data = tgct_cisplatin_surv_df,
size = 1, #change line size
palette = c('purple', 'limegreen'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6, risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Resistant', 'Sensitive'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 3100, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
tgct_cisplatin_ks_test <- ks.test(tgct_cisplatin_surv_df$tgct_surv_times[tgct_cisplatin_surv_df$X1 == 1],
tgct_cisplatin_surv_df$tgct_surv_times[tgct_cisplatin_surv_df$X1 == 0])
tgct_cisplatin_ks_test_p_value <- round(tgct_cisplatin_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(tgct_cisplatin_surv_df, aes(x = tgct_cisplatin_surv_df$tgct_surv_times, fill = factor(tgct_cisplatin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('purple', 'limegreen'), labels = c('Resistant', 'Sensitive')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 4000, y = 1.9e-4,
label = paste0('KS\np = ', tgct_cisplatin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/tgct_cisplatin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## brca w doxorubicin 45 ----
brca_doxorubicin_surv_df <- read.table('Survival_Data/brca_doxorubicin_surv_df.txt', header = TRUE)
brca_doxorubicin_surv_df$X1 <- swap(brca_doxorubicin_surv_df$X1, c('sensitive', 'resistant'), c('resistant', 'sensitive'))
#fit survival curves
brca_doxorubicin_fit <- survfit(Surv(brca_surv_times, brca_status) ~ X1,
data = brca_doxorubicin_surv_df)
#plot them
surv_plot <- ggsurvplot(brca_doxorubicin_fit, data = brca_doxorubicin_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 5*365, linetype = 'dashed') +
annotate('text', x = 2300, y = 0.25,
label = '5-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
brca_doxorubicin_ks_test <- ks.test(brca_doxorubicin_surv_df$brca_surv_times[brca_doxorubicin_surv_df$X1 == 'sensitive'],
brca_doxorubicin_surv_df$brca_surv_times[brca_doxorubicin_surv_df$X1 == 'resistant'])
brca_doxorubicin_ks_test_p_value <- round(brca_doxorubicin_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(brca_doxorubicin_surv_df, aes(x = brca_doxorubicin_surv_df$brca_surv_times, fill = factor(brca_doxorubicin_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 3000, y = 4e-4,
label = paste0('KS\np = ', brca_doxorubicin_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/brca_doxorubicin_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## luad w etoposide 6 ----
luad_etoposide_surv_df <- read.table('Survival_Data/luad_etoposide_surv_df.txt', header = TRUE)
luad_etoposide_surv_df$X1 <- swap(luad_etoposide_surv_df$X1, c('resistant', 'sensitive'), c('sensitive', 'resistant'))
#fit survival curves
luad_etoposide_fit <- survfit(Surv(luad_surv_times, luad_status) ~ X1,
data = luad_etoposide_surv_df)
#plot them
surv_plot <- ggsurvplot(luad_etoposide_fit, data = luad_etoposide_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 3*365, linetype = 'dashed') +
annotate('text', x = 1300, y = 0.25,
label = '3-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
luad_etoposide_ks_test <- ks.test(luad_etoposide_surv_df$luad_surv_times[luad_etoposide_surv_df$X1 == 'sensitive'],
luad_etoposide_surv_df$luad_surv_times[luad_etoposide_surv_df$X1 == 'resistant'])
luad_etoposide_ks_test_p_value <- round(luad_etoposide_ks_test$p.value, digits = 6)
#density plot
dens_plot <- ggplot(luad_etoposide_surv_df, aes(x = luad_etoposide_surv_df$luad_surv_times, fill = factor(luad_etoposide_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 300, y = 1e-3,
label = paste0('KS\np = ', luad_etoposide_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/luad_etoposide_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## blca w gemcitabine 29 ----
blca_gemcitabine_surv_df <- read.table('Survival_Data/blca_gemcitabine_surv_df.txt', header = TRUE)
#fit survival curves
blca_gemcitabine_fit <- survfit(Surv(blca_surv_times, blca_status) ~ X1,
data = blca_gemcitabine_surv_df)
#plot them
surv_plot <- ggsurvplot(blca_gemcitabine_fit, data = blca_gemcitabine_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 3*365, linetype = 'dashed') +
annotate('text', x = 1700, y = 0.25,
label = '3-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
blca_gemcitabine_ks_test <- ks.test(blca_gemcitabine_surv_df$blca_surv_times[blca_gemcitabine_surv_df$X1 == 'sensitive'],
blca_gemcitabine_surv_df$blca_surv_times[blca_gemcitabine_surv_df$X1 == 'resistant'])
blca_gemcitabine_ks_test_p_value <- round(blca_gemcitabine_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(blca_gemcitabine_surv_df, aes(x = blca_gemcitabine_surv_df$blca_surv_times, fill = factor(blca_gemcitabine_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('limegreen', 'purple'), labels = c('Sensitive', 'Resistant')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 2000, y = 0.0008,
label = paste0('KS\np = ', blca_gemcitabine_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/blca_gemcitabine_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## chol w gemcitabine 5 ----
chol_gemcitabine_surv_df <- read.table('Survival_Data/chol_gemcitabine_surv_df.txt', header = TRUE)
#fit survival curves
chol_gemcitabine_fit <- survfit(Surv(chol_surv_times, chol_status) ~ X1,
data = chol_gemcitabine_surv_df)
#plot them
surv_plot <- ggsurvplot(chol_gemcitabine_fit, data = chol_gemcitabine_surv_df,
size = 1, #change line size
palette = c('purple', 'limegreen'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Resistant', 'Sensitive'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 3*365, linetype = 'dashed') +
annotate('text', x = 1300, y = 0.25,
label = '3-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
chol_gemcitabine_ks_test <- ks.test(chol_gemcitabine_surv_df$chol_surv_times[chol_gemcitabine_surv_df$X1 == 'sensitive'],
chol_gemcitabine_surv_df$chol_surv_times[chol_gemcitabine_surv_df$X1 == 'resistant'])
chol_gemcitabine_ks_test_p_value <- round(chol_gemcitabine_ks_test$p.value, digits = 6)
#density plot
dens_plot <- ggplot(chol_gemcitabine_surv_df, aes(x = chol_gemcitabine_surv_df$chol_surv_times, fill = factor(chol_gemcitabine_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('purple', 'limegreen'), labels = c('Resistant', 'Sensitive')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 400, y = 0.0008,
label = paste0('KS\np = ', chol_gemcitabine_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/chol_gemcitabine_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## lihc w gemcitabine 8 ----
lihc_gemcitabine_surv_df <- read.table('Survival_Data/lihc_gemcitabine_surv_df.txt', header = TRUE)
#fit survival curves
lihc_gemcitabine_fit <- survfit(Surv(lihc_surv_times, lihc_status) ~ X1,
data = lihc_gemcitabine_surv_df)
#plot them
surv_plot <- ggsurvplot(lihc_gemcitabine_fit, data = lihc_gemcitabine_surv_df,
size = 1, #change line size
palette = c('purple', 'limegreen'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Resistant', 'Sensitive'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 3*365, linetype = 'dashed') +
annotate('text', x = 1300, y = 0.25,
label = '3-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
surv_table_new <- surv_plot$table + labs(title = 'Number at Risk of Recurrence') +
theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'white'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
plot.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#ks test for dist curves
lihc_gemcitabine_ks_test <- ks.test(lihc_gemcitabine_surv_df$lihc_surv_times[lihc_gemcitabine_surv_df$X1 == 'sensitive'],
lihc_gemcitabine_surv_df$lihc_surv_times[lihc_gemcitabine_surv_df$X1 == 'resistant'])
lihc_gemcitabine_ks_test_p_value <- round(lihc_gemcitabine_ks_test$p.value, digits = 2)
#density plot
dens_plot <- ggplot(lihc_gemcitabine_surv_df, aes(x = lihc_gemcitabine_surv_df$lihc_surv_times, fill = factor(lihc_gemcitabine_surv_df$X1))) +
geom_density(alpha = 0.5) + scale_fill_manual(values = c('purple', 'limegreen'), labels = c('Resistant', 'Sensitive')) + theme_bw() +
labs(x = 'Recurrence-Free Survival (d)', y = 'Density', fill = '') +
annotate('text', x = 275, y = 0.0045,
label = paste0('KS\np = ', lihc_gemcitabine_ks_test_p_value),
size = 5) + theme(legend.position = 'bottom',
axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 16, face = 'bold', colour = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
#plot with patchwork
tiff(filename = 'Images/lihc_gemcitabine_surv.tiff', units = 'in', width = 10, height = 6, res = 300)
layout <- '
AAACCC
AAACCC
AAACCC
AAACCC
AAACCC
BBBCCC'
surv_plot_new + surv_table_new + dens_plot + plot_layout(design = layout)
dev.off()
## luad w gemcitabine 13 ----
luad_gemcitabine_surv_df <- read.table('Survival_Data/luad_gemcitabine_surv_df.txt', header = TRUE)
luad_gemcitabine_surv_df$X1 <- swap(luad_gemcitabine_surv_df$X1, c('sensitive', 'resistant'), c('resistant', 'sensitive'))
#fit survival curves
luad_gemcitabine_fit <- survfit(Surv(luad_surv_times, luad_status) ~ X1,
data = luad_gemcitabine_surv_df)
#plot them
surv_plot <- ggsurvplot(luad_gemcitabine_fit, data = luad_gemcitabine_surv_df,
size = 1, #change line size
palette = c('limegreen', 'purple'), #custom color scheme
conf.int = TRUE, # add CIs
pval = TRUE,
pval.method = TRUE,
pval.size = 6,
risk.table = TRUE, # add p-value
legend = 'bottom',
legend.labs = c('Sensitive', 'Resistant'),
xlab = 'Time (d)',
ylab = 'Proportion\nRecurrence-Free',
conf.int.style = 'ribbon',
ggtheme = theme_bw())
#customize and ready for patchwork
surv_plot_new <- surv_plot$plot + geom_vline(xintercept = 3*365, linetype = 'dashed') +
annotate('text', x = 900, y = 0.25,
label = '3-year\nRFS', size = 6, fontface = 2) + theme(axis.title.x = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.x = element_text(size = 14, face = 'bold', colour = 'black'),
axis.title.y = element_text(size = 16, face = 'bold', colour = 'black'),
axis.text.y = element_text(size = 14, face = 'bold', colour = 'black'),
legend.text = element_text(size = 14, face = 'bold', colour = 'black'),
legend.title = element_text(size = 1, face = 'bold', colour = 'white'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())