#!/usr/bin/Rscript getwd() setwd('~/git/covid_analysis/') getwd() ############################################################ # TASK: Loess plots for days into hospital till T1 ############################################################ #========================================================== #============= # input:source data #============= source("read_data.R") # clear unwanted variables rm(my_data, wf_data, lf_data) #============= # Output #============= output_plots_loess_hosp = paste0(outdir_plots, "output_plots_v3_loess_hosp.pdf") #%%======================================================== #===================== # data for plots #===================== # remove PF table(lf_data_loess$mediator) lf_loess = lf_data_loess[lf_data_loess$mediator!= "PF",] table(lf_loess$mediator) #%======================================================= hosp_days_min = min(lf_loess$days_from_hospitalization_t1); hosp_days_min hosp_days_max = max(lf_loess$days_from_hospitalization_t1);hosp_days_max my_xscale_hosp = seq(hosp_days_min , hosp_days_max, 5) my_xscale_hosp ##################################################################### # 95% CI: t1_data # days_from_hospitalization_t1 ##################################################################### lf_loess_t1 = lf_loess[lf_loess$timepoint == "t1",] # Output plots as one pdf cat("Output plots will be in:", output_plots_loess_hosp) pdf(output_plots_loess_hosp, width = 15, height = 8) #----------- # linear #----------- p1_hosp = ggplot(lf_loess_t1, aes(x = days_from_hospitalization_t1 , y = value , colour = factor(outcomes))) + #geom_point() + geom_smooth(method = "loess", size = 1.5, na.rm = T) + facet_wrap(~mediator, nrow = 2, scales = "free_y")+ labs(title = "Hospital days into t1: Linear scale and 95% CI" , x = "Days from hospitalisation to t1" , y = "T1 Levels")+ scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ scale_colour_discrete(name = "Patient outcome" , labels = c("Death", "Recovered"))+ theme(axis.text.x = element_text(size = 13) , axis.text.y = element_text(size = 13 , angle = 0 , hjust = 1 , vjust = 0) , axis.title.x = element_text(size = 13) , axis.title.y = element_text(size = 13) , plot.title = element_text(size = 15, hjust = 0.5) , strip.text.x = element_text(size = 13, colour = "black") , legend.title = element_text(color = "black", size = 13) , legend.text = element_text(size = 13) , legend.position = "right" , legend.direction = "vertical") p1_hosp #----------- # log #----------- p2_hosp = ggplot(lf_loess_t1, aes(x = days_from_hospitalization_t1 , y = value , colour = factor(outcomes))) + scale_y_log10()+ #geom_point() + geom_smooth(method = "loess", size = 1.5, na.rm = T) + facet_wrap(~mediator, nrow = 2, scales = "free_y")+ labs(title = "Hospital days into t1: Log scale and 95% CI" , x = "Days from hospitalisation to t1" , y = "T1 Levels (Log10)")+ scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ scale_colour_discrete(name = "Patient outcome" , labels = c("Death", "Recovered"))+ theme(axis.text.x = element_text(size = 13) , axis.text.y = element_text(size = 13 , angle = 0 , hjust = 1 , vjust = 0) , axis.title.x = element_text(size = 13) , axis.title.y = element_text(size = 13) , plot.title = element_text(size = 15, hjust = 0.5) , strip.text.x = element_text(size = 13, colour = "black") , legend.title = element_text(color = "black", size = 13) , legend.text = element_text(size = 13) , legend.position = "right" , legend.direction = "vertical") p2_hosp ##################################################################### # 50% CI: t1_data # days_from_hospitalization_t1 ##################################################################### #----------- # linear #----------- p3_hosp = ggplot(lf_loess_t1, aes(x = days_from_hospitalization_t1 , y = value , colour = factor(outcomes))) + #geom_point() + geom_smooth(method = "loess", size = 1.5, na.rm = T, level = 0.50) + facet_wrap(~mediator, nrow = 2, scales = "free_y")+ labs(title = "Hospital days into t1: Linear scale and 50% CI" , x = "Days from hospitalisation to t1" , y = "T1 Levels") + scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ scale_colour_discrete(name = "Patient outcome" , labels = c("Death", "Recovered"))+ theme(axis.text.x = element_text(size = 13) , axis.text.y = element_text(size = 13 , angle = 0 , hjust = 1 , vjust = 0) , axis.title.x = element_text(size = 13) , axis.title.y = element_text(size = 13) , plot.title = element_text(size = 15, hjust = 0.5) , strip.text.x = element_text(size = 13, colour = "black") , legend.title = element_text(color = "black", size = 13) , legend.text = element_text(size = 13) , legend.position = "right" , legend.direction = "vertical") p3_hosp #----------- # log #----------- p4_hosp = ggplot(lf_loess_t1, aes(x = days_from_hospitalization_t1 , y = value , colour = factor(outcomes))) + scale_y_log10()+ #geom_point() + geom_smooth(method = "loess", size = 1.5, na.rm = T, level = 0.50) + facet_wrap(~mediator, nrow = 2, scales = "free_y")+ labs(title = "Hospital days into t1: Log scale and 50% CI" , x = "Days from hospitalisation to t1" , y = "T1 Levels (Log10)")+ scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ scale_colour_discrete(name = "Patient outcome" , labels = c("Death", "Recovered"))+ theme(axis.text.x = element_text(size = 13) , axis.text.y = element_text(size = 13 , angle = 0 , hjust = 1 , vjust = 0) , axis.title.x = element_text(size = 13) , axis.title.y = element_text(size = 13) , plot.title = element_text(size = 15, hjust = 0.5) , strip.text.x = element_text(size = 13, colour = "black") , legend.title = element_text(color = "black", size = 13) , legend.text = element_text(size = 13) , legend.position = "right" , legend.direction = "vertical") p4_hosp dev.off() ##################################################################### # 95% CI: Combined data *** only if required # days_from_hospitalization_t1 ##################################################################### #----------- # linear #----------- #p1_all_hosp = ggplot(lf_loess, aes(x = days_from_hospitalization_t1 # , y = value # , colour = factor(outcomes))) + # #geom_point() + # geom_smooth(method = "loess", size = 1.5, na.rm = T, level = 0.90) + # facet_wrap(~mediator, nrow = 2, scales = "free_y")+ # labs(title = "Hospital days into t1: linear scale and 95% CI" # , x = "Days from hospitalisation to t1" # , y = "Combined Levels")+ # scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ # scale_colour_discrete(name = "Patient outcome" # , labels = c("Death", "Recovered")) #p1_all_hosp #----------- # log #----------- #p2_all_hosp = ggplot(lf_loess, aes(x = days_from_hospitalization_t1 # , y = value # , colour = factor(outcomes))) + # scale_y_log10()+ # #geom_point() + # geom_smooth(method = "loess", size = 1.5, na.rm = T) + # facet_wrap(~mediator, nrow = 2, scales = "free_y")+ # labs(title = "Hospital days into t1: Log scale and 95% CI" # , x = "Days from hospitalisation to t1" # , y = "Combined Levels (Log10)")+ # scale_x_continuous(breaks = my_xscale_hosp, limits = c(hosp_days_min , hosp_days_max))+ # scale_colour_discrete(name = "Patient outcome" # , labels = c("Death", "Recovered")) #p2_all_hosp