added output_figure.R for ggridges plot at T1
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2 changed files with 213 additions and 1 deletions
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output_figures.R
Executable file
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output_figures.R
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#!/usr/bin/Rscript
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getwd()
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setwd('~/git/covid_analysis/')
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getwd()
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############################################################
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# TASK: ggridges at T1 only
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# selected figure for manuscript
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############################################################
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# source data
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source("read_data.R")
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# clear unwanted variables
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rm(my_data)
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############################################################
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#=============
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# Output
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#=============
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output_dist_t1 = paste0(outdir_plots, "output_dist_t1_v3.svg")
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output_dist_t1_f = paste0(outdir_plots, "output_dist_t1_v3_f.svg")
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#%%========================================================
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# read file
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lf_data = read.csv(infile_icu_lf , stringsAsFactors = F)
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dim(lf_data)
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#=====================
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# data for plots: LF
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#=====================
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# omit PF
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table(lf_data$mediator)
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expected_rows = nrow(lf_data) - table(lf_data$mediator)[["PF"]]; expected_rows
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expected_cols = length(lf_data); expected_cols
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lf = lf_data[lf_data$mediator!="PF",]
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table(lf$mediator)
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if ( nrow(lf) == expected_rows && length(lf) == expected_cols ){
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cat ("PASS: dimensions match in subsetted data"
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, "\nnrows:", nrow(lf)
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, "\nncols:", length(lf))
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}else{
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cat ("FAIL: dimensions mismatch. Check expected rows and cols calculations"
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, "\nExpected rows:", expected_rows
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, "\nGot:", nrow(lf)
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, "\nExpected cols:", expected_cols
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, "\nGot:", length(lf))
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}
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dim(lf); str(lf)
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levels(factor(lf$mediator)); table(lf$mediator)
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#---------------------
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# nice mediator names
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#---------------------
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nice_mediator_names1 = c(Angiopoietin2 = "ANG-2"
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, PSelectin = "sP-Selectin"
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, sESelectin = "sE-Selectin"
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, sICAM1="sICAM-1"
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, sRAGE= "sRAGE"
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, sVCAM1="sVCAM-1")
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# assign nice mediator names
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lf$mediator_names1 <- as.character(nice_mediator_names1[lf$mediator])
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#---------------------
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# nice names without leading 's'
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#---------------------
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nice_mediator_names2 = c(Angiopoietin2 = "ANG-2"
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, PSelectin = "P-Selectin"
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, sESelectin = "E-Selectin"
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, sICAM1="ICAM-1"
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, sRAGE= "RAGE"
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, sVCAM1="VCAM-1")
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# assign nice mediator names without leading 's'
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lf$mediator_names2 <- as.character(nice_mediator_names2[lf$mediator])
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dim(lf); str(lf)
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levels(factor(lf$mediator)); table(lf$mediator)
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#-------------------------------
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# generate order for mediators
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#------------------------------
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mediator_order = c("Angiopoietin2" = 2
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, "PSelectin" = 5
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, "sESelectin" = 6
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, "sICAM1" = 3
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, "sRAGE" = 1
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, "sVCAM1" = 4)
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# reorder mediators as required
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lf$order_mediators <- mediator_order[lf$mediator]
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table(lf$order_mediators)
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# reorder the df according to order_mediators: not needed as ggridges ignores this!
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#table(lf$mediator)
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#lf = lf[order(lf$order_mediators),]
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#table(lf$mediator)
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lf$outcome_category = as.factor(lf$outcomes)
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levels(lf$outcome_category); str(lf$outcome_category)
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lf$mediator_names1 = as.factor(lf$mediator_names1)
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str(lf$mediator_names1); levels(lf$mediator_names1); table(lf$mediator_names1)
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lf$mediator_names2 = as.factor(lf$mediator_names2)
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str(lf$mediator_names2); levels(lf$mediator_names2); table(lf$mediator_names2)
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#%%========================================================
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# count na in mediator col
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if (table(is.na(lf$mediator)) == nrow(lf)){
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print("PASS: No NAs detected, lf data is good for plotting")
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}else{
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print("FAIL: NAs detected in mediator columna. Check source formatting for lf data")
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#lf <- lf[!is.na(lf$mediator),]
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#head(lf); str(lf)
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quit()
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}
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#====================================
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# Output plot: Distribution at T1
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#====================================
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lf_t1 = dplyr::filter(lf, timepoint == "t1")
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my_title_dist_t1 = "Distributions of mediators at T1"
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#x_axis_text = expression("Log"[10])
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x_axis_text = expression(Log[10]~(Levels))
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#-----------------
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# ggrides: at T1
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#-----------------
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cat("Output plots will be in:", output_dist_t1)
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svg(output_dist_t1, width = 15, height = 15)
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p_dist_t1 = ggplot(lf_t1, aes(x = log10(value)
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#, y = mediator))+
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, y = fct_reorder(mediator_names1, order_mediators, .fun = sum))) +
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geom_density_ridges(aes(fill = factor(outcomes))
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, alpha = 0.6) +
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theme(axis.text.x = element_text(size = 22)
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, axis.text.y = element_text(size = 22
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.x = element_text(size = 22)
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, axis.title.y = element_text(size = 22)
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#, plot.title = element_text(size = 15, hjust = 0.5)
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, strip.text.x = element_text(size = 22, colour = "black")
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#, legend.title = element_text(color = "black", size = 22)
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, legend.title = element_blank()
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, legend.text = element_text(size = 25)
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#, legend.position = "right"
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, legend.position = c(0.8, 0.95)
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, legend.direction = "vertical") +
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labs(title = ""
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#, x = "Log10 (Levels)"
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, x = x_axis_text
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, y = "") +
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#scale_fill_discrete(name = "Patient outcome", labels = c("Died", "Recovered"))
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scale_fill_discrete(name = "Patient outcome", labels = c("Non-survivors", "Survivors")) +
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guides(fill = guide_legend(reverse = T))
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p_dist_t1
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dev.off()
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# test
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#foo = p_dist_t1 + guides(fill = guide_legend(reverse = T))
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#foo
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###################################################################################
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#-----------------
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# ggrides: at T1, version 2
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# without 's' in mediator names
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#-----------------
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cat("Output plots will be in:", output_dist_t1_f)
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svg(output_dist_t1_f, width = 15, height = 15)
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p_dist_t1_v3 = ggplot(lf_t1, aes(x = log10(value)
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#, y = mediator))+
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, y = fct_reorder(mediator_names2, order_mediators, .fun = sum))) +
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geom_density_ridges(aes(fill = factor(outcomes))
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, alpha = 0.6) +
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theme(axis.text.x = element_text(size = 22)
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, axis.text.y = element_text(size = 22
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.x = element_text(size = 22)
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, axis.title.y = element_text(size = 22)
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#, plot.title = element_text(size = 15, hjust = 0.5)
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, strip.text.x = element_text(size = 22, colour = "black")
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#, legend.title = element_text(color = "black", size = 22)
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, legend.title = element_blank()
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, legend.text = element_text(size = 25)
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#, legend.position = "right"
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, legend.position = c(0.8, 0.95)
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, legend.direction = "vertical") +
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labs(title = ""
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#, x = "Log10 (Levels)"
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, x = x_axis_text
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, y = "") +
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scale_fill_discrete(name = "Patient outcome", labels = c("Non-survivors", "Survivors")) +
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guides(fill = guide_legend(reverse = T))
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p_dist_t1_v3
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dev.off()
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###################################################################################
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@ -12,7 +12,7 @@ source("Header_TT.R")
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datadir = "~/git/covid_data/"
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outdir = "~/git/covid_data/output/"
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outdir_plots = "~/git/covid_data/output/plots/"
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outdir_plots_send = "~/git/covid_data/output/plots/to_send"
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#outdir_plots_send = "~/git/covid_data/output/plots/to_send"
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outdir_stats = "~/git/covid_data/output/stats/"
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#==========================================================
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