generating plots for all sample types withoout stats

This commit is contained in:
Tanushree Tunstall 2020-10-29 18:50:25 +00:00
parent c26171d12c
commit 540b6c5bf7
2 changed files with 217 additions and 136 deletions

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@ -7,3 +7,5 @@ library(rstatix)
library(Hmisc) library(Hmisc)
library(qwraps2) library(qwraps2)
source("legend_adjustment.R") source("legend_adjustment.R")
# https://www.datanovia.com/en/blog/how-to-add-p-values-onto-a-grouped-ggplot-using-the-ggpubr-r-package/#perform-all-pairwise-comparisons

351
boxplot.R
View file

@ -22,150 +22,229 @@ outfile_bp = paste0("boxplots_", my_sample_type, ".pdf")
output_boxplot = paste0(outdir_plots, outfile_bp); output_boxplot output_boxplot = paste0(outdir_plots, outfile_bp); output_boxplot
#=============================== #===============================
# data assignment for stats # data assignment for plots
#================================ #================================
wf = serum_wf[serum_wf$flustat == 1,] #wf_fp_npa = npa_wf[npa_wf$flustat == 1,]
lf = serum_lf[serum_lf$flustat == 1,] lf_fp_npa = npa_lf[npa_lf$flustat == 1,]
lf$timepoint = paste0("t", lf$timepoint) lf_fp_npa$timepoint = paste0("t", lf_fp_npa$timepoint)
lf_fp_npa$timepoint = as.factor(lf_fp_npa$timepoint)
lf_fp_npa$obesity = as.factor(lf_fp_npa$obesity)
#================== #wf_fp_sam = samm_wf[samm_wf$flustat == 1,]
# Data for plotting lf_fp_sam = sam_lf[sam_lf$flustat == 1,]
#================== lf_fp_sam$timepoint = paste0("t", lf_fp_sam$timepoint)
# convert these to factor lf_fp_sam$timepoint = as.factor(lf_fp_sam$timepoint)
lf$obesity = as.factor(lf$obesity) lf_fp_sam$obesity = as.factor(lf_fp_sam$obesity)
lf$timepoint = as.factor(lf$timepoint)
#wf_fp_serum = serum_wf[serum_wf$flustat == 1,]
lf_fp_serum = serum_lf[serum_lf$flustat == 1,]
lf_fp_serum$timepoint = paste0("t", lf_fp_serum$timepoint)
lf_fp_serum$timepoint = as.factor(lf_fp_serum$timepoint)
lf_fp_serum$obesity = as.factor(lf_fp_serum$obesity)
######################################################################## ########################################################################
my_comparisons <- list( c("0", "1") )
########################################################################
lf_test = lf[lf$mediator == "eotaxin",]
str(lf_test)
p = ggplot(lf_test, aes(x = timepoint, y = value, fill = obesity )) +
geom_boxplot(width = 0.5)
p
# see default ggplot palette
ggplot_build(p)$data
p + stat_compare_means(comparisons = my_comparisons
, method = "wilcox.test"
, paired = F
, label = "p.format")
########################################################################
library(ggpubr)
library(rstatix)
# stats
stat.test <- lf_test %>%
group_by(timepoint) %>%
wilcox_test(value ~ obesity) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance("p.adj")
stat.test
# add stats to grouped boxplots
str(lf_test)
lf_test$obesity = as.factor(lf_test$obesity) # ensure factor
bxp <- ggboxplot(lf_test, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D"))
bxp
stat.test <- stat.test %>%
add_xy_position(x = "timepoint", dodge = 0.8)
bxp + stat_pvalue_manual(
stat.test, label = "p", tip.length = 0
)
################################
lf_test2 = lf[order(lf$mediator),] # 2 meds
lf_test2 = lf_test2[1:798,]
table(lf_test2$mediator)
str(lf_test2)
stat.test <- lf_test2 %>%
group_by(timepoint, mediator) %>%
wilcox_test(value ~ obesity, paired = F) %>%
#adjust_pvalue(method = "bonferroni") %>%
#add_significance("p.adj")
add_significance("p")
stat.test
bxp <- ggboxplot(lf_test2, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, scales = "free_y")
bxp
stat.test <- stat.test %>%
add_xy_position(x = "timepoint", dodge = 0.8)
bxp + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
########################################################################
lf_comp = lf[-which(is.na(lf$value)),]
lf_test_comp = lf_comp[lf_comp$mediator == "eotaxin",]
str(lf_comp)
p2 = ggplot(lf_test_comp, aes(x = timepoint, y = value, fill = obesity )) +
geom_boxplot(width = 0.5)
p2
########################################################################
# Output plots as one pdf
cat("Output plots will be in:", output_boxplot)
pdf(output_boxplot, width = 25, height = 15)
#stats data
str(lf)
stat.test <- lf %>%
group_by(timepoint, mediator) %>%
wilcox_test(value ~ obesity, paired = F) %>%
#adjust_pvalue(method = "bonferroni") %>%
#add_significance("p.adj")
add_significance("p")
stat.test
bxp <- ggboxplot(lf, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
scale_y_log10()
bxp
bxp + stat.test <- stat.test %>%
add_xy_position(x = "timepoint", dodge = 0.8)
bxp + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
dev.off()
######output
# Output plots as one pdf
cat("Output plots will be in:", output_boxplot) cat("Output plots will be in:", output_boxplot)
pdf(output_boxplot, width = 20, height = 15) pdf(output_boxplot, width = 20, height = 15)
my_title1 = "Boxplots: serum"
bxp <- ggboxplot(lf, x = "timepoint", y = "value", #=======================================================================
# SAM
#=======================================================================
if (is.factor(lf_fp_sam$timepoint) && is.factor(lf_fp_sam$timepoint)){
cat ("PASS: required groups are factors")
}
table(lf_fp_sam$mediator)
lf_fp_sam = lf_fp_sam[!lf_fp_sam$mediator == "vitd",]
#------------------------------------------
title_sam_linear = "Boxplot: sam (Linear)"
#-----------------------------------------
bxp_sam_linear <- ggboxplot(lf_fp_sam, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) + color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+ facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
scale_y_log10() #scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
bxp + theme(axis.text.x = element_text(size = 15) , axis.text.y = element_text(size = 15
, axis.text.y = element_text(size = 15 , angle = 0
, angle = 0 , hjust = 1
, hjust = 1 , vjust = 0)
, vjust = 0) , axis.title.x = element_text(size = 15)
, axis.title.x = element_text(size = 15) , axis.title.y = element_text(size = 15)
, axis.title.y = element_text(size = 15) , plot.title = element_text(size = 20, hjust = 0.5)
, plot.title = element_text(size = 20, hjust = 0.5) , strip.text.x = element_text(size = 15, colour = "black")
, strip.text.x = element_text(size = 15, colour = "black") , legend.title = element_text(color = "black", size = 20)
, legend.title = element_text(color = "black", size = 20) , legend.text = element_text(size = 15)
, legend.text = element_text(size = 15) , legend.direction = "horizontal") +
, legend.direction = "horizontal") + labs(title = title_sam_linear
labs(title = my_title1
, x = "" , x = ""
, y = "Levels (Log10)") , y = "Levels")
#shift_legend2(bxp)
bxp_sam_linear
#------------------------------------
title_sam_log = "Boxplot: sam (Log)"
#-----------------------------------
bxp_sam_log <- ggboxplot(lf_fp_sam, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
, axis.text.y = element_text(size = 15
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = 15)
, axis.title.y = element_text(size = 15)
, plot.title = element_text(size = 20, hjust = 0.5)
, strip.text.x = element_text(size = 15, colour = "black")
, legend.title = element_text(color = "black", size = 20)
, legend.text = element_text(size = 15)
, legend.direction = "horizontal") +
labs(title = title_sam_log
, x = ""
, y = "Levels (Log)")
bxp_sam_log
#=======================================================================
# SERUM
#=======================================================================
if (is.factor(lf_fp_serum$timepoint) && is.factor(lf_fp_serum$timepoint)){
cat ("PASS: required groups are factors")
}
table(lf_fp_serum$mediator)
#------------------------------------------
title_serum_linear = "Boxplot: serum (Linear)"
#-----------------------------------------
bxp_serum_linear <- ggboxplot(lf_fp_serum, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
#scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
, axis.text.y = element_text(size = 15
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = 15)
, axis.title.y = element_text(size = 15)
, plot.title = element_text(size = 20, hjust = 0.5)
, strip.text.x = element_text(size = 15, colour = "black")
, legend.title = element_text(color = "black", size = 20)
, legend.text = element_text(size = 15)
, legend.direction = "horizontal") +
labs(title = title_serum_linear
, x = ""
, y = "Levels")
bxp_serum_linear
#------------------------------------
title_serum_log = "Boxplot: serum (Log)"
#-----------------------------------
bxp_serum_log <- ggboxplot(lf_fp_serum, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
, axis.text.y = element_text(size = 15
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = 15)
, axis.title.y = element_text(size = 15)
, plot.title = element_text(size = 20, hjust = 0.5)
, strip.text.x = element_text(size = 15, colour = "black")
, legend.title = element_text(color = "black", size = 20)
, legend.text = element_text(size = 15)
, legend.direction = "horizontal") +
labs(title = title_serum_log
, x = ""
, y = "Levels (Log)")
bxp_serum_log
#=======================================================================
# NPA
#=======================================================================
if (is.factor(lf_fp_npa$timepoint) && is.factor(lf_fp_npa$timepoint)){
cat ("PASS: required groups are factors")
}
table(lf_fp_npa$mediator)
head(lf_fp_npa$value[lf_fp_npa$mediator == "vitd"])
lf_fp_npa = lf_fp_npa[!lf_fp_npa$mediator == "vitd",]
#------------------------------------------
title_npa_linear = "Boxplot: NPA (Linear)"
#-----------------------------------------
bxp_npa_linear <- ggboxplot(lf_fp_npa, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
#scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
, axis.text.y = element_text(size = 15
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = 15)
, axis.title.y = element_text(size = 15)
, plot.title = element_text(size = 20, hjust = 0.5)
, strip.text.x = element_text(size = 15, colour = "black")
, legend.title = element_text(color = "black", size = 20)
, legend.text = element_text(size = 15)
, legend.direction = "horizontal") +
labs(title = title_npa_linear
, x = ""
, y = "Levels")
bxp_npa_linear
#------------------------------------
title_npa_log = "Boxplot: NPA (Log)"
#-----------------------------------
bxp_npa_log <- ggboxplot(lf_fp_npa, x = "timepoint", y = "value",
color = "obesity", palette = c("#00BFC4", "#F8766D")) +
facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = F)+
scale_y_log10() +
theme(axis.text.x = element_text(size = 15)
, axis.text.y = element_text(size = 15
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = 15)
, axis.title.y = element_text(size = 15)
, plot.title = element_text(size = 20, hjust = 0.5)
, strip.text.x = element_text(size = 15, colour = "black")
, legend.title = element_text(color = "black", size = 20)
, legend.text = element_text(size = 15)
, legend.direction = "horizontal") +
labs(title = title_npa_log
, x = ""
, y = "Levels (Log)")
bxp_npa_log
dev.off() dev.off()
#==========================================================================
#------------------------------------
title_npa_log_stats = "Boxplot: NPA (Log) + stats"
#-----------------------------------
stat.test <- lf_fp_npa %>%
group_by(timepoint, mediator) %>%
wilcox_test(value ~ obesity, paired = F) %>%
add_significance("p")
stat.test
stat.test <- stat.test %>%
add_xy_position(x = "timepoint", dodge = 0.8)
bxp_npa_linear + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
bxp_npa_log + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
dev.off()