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boxplot_with_stats_test.R
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264
boxplot_with_stats_test.R
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#!/usr/bin/Rscript
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getwd()
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setwd("~/git/mosaic_2020/")
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getwd()
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############################################################
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# TASK: boxplots at T1
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# FIXME: currently not rendering, problem with NAs for stats?
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############################################################
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#=============
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# Input
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#=============
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source("boxplot_linear.R")
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#######################################################
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med_names = c("eotaxin3", "il12p70", "itac", "il13")
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lf_test = lf_fp_npa[lf_fp_npa$mediator%in%med_names,]
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mediators = levels(as.factor(lf_test$mediator))
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mediators = levels(as.factor(lf_fp_npa$mediator))
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lf_test = lf_fp_npa
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plots <- list()
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for (i in mediators) {
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single=lf_test[lf_test$mediator==i,]
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max_y = max(single$value, na.rm = T)
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cat("Plotting:", i, "max_y:", max_y, "\n")
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p2 = ggplot(single)+ geom_boxplot(aes(x = timepoint
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, y = value
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, color = obesity
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#, palette = c("#00BFC4", "#F8766D")
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))+
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scale_colour_manual(values=c("blue", "red")) +
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theme(axis.text.x = element_text(size = 15)
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#axis.text.x = element_blank()
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, axis.text.y = element_text(size = 15
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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_blank()
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, axis.title.y = element_blank()
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, legend.position = "none"
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, plot.subtitle = element_text(size = 20, hjust = 0.5)
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, plot.title = element_text(size = 20, hjust = 0.5)) +
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labs(title = i
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#, subtitle = "test2"
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)
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stat_npa2 <- single %>%
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group_by(timepoint, mediator) %>%
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wilcox_test(value ~ obesity, paired = F) %>%
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add_significance("p")
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stat_npa2
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stat_npa2 <- stat_npa2 %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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p2 = p2 + stat_pvalue_manual(stat_npa2
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#, y.position = max_y
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, label = "{p} {p.signif}"
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, hide.ns=T
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, tip.length = 0)+
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scale_y_continuous(expand = expansion(mult = c(0.05, 0.25))) +
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plots[[i]] <- p2
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}
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#============================
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# combine: cowplot_plot_grid
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#============================
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#cowplot::plot_grid(plotlist=plots, align = 'hv', ncol=2, nrow=2)
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pdf("test.pdf", width = 22, height = 16)
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cowplot::plot_grid(plotlist=plots, align = 'hv', ncol=7, nrow=5)
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dev.off()
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#===========================
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# combine: ggpubr::ggarrange
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#===========================
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pdf("test2.pdf", width = 22, height = 16)
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npa_plot<- ggpubr::ggarrange(plotlist = plots, align = "hv"
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, ncol = 7
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, nrow = 5
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, common.legend = T)
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npa_plot
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annotate_figure(npa_plot,
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top = text_grob("NPA", color = "purple", face = "bold", size = 14),
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bottom = text_grob("Mosaic data\nFlu positive adults (n=133)"
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, color = "blue",
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hjust = 1, x = 0.98, face = "italic", size = 10),
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left = text_grob("Levels (pg/ml)", color = "black", rot = 90, size = 18),
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#right = "I'm done, thanks :-)!",
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#fig.lab = "Figure 1", fig.lab.face = "bold"
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)
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##################################################################
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#=======
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# facet
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#=======
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#--------
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# wilcox stats
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#--------
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stat_npa3 <- lf_test %>%
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group_by(timepoint, mediator) %>%
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wilcox_test(value ~ obesity, paired = F) %>%
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add_significance("p")
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stat_npa3
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stat_npa3$p_format = round(stat_npa3$p, 3)
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stat_npa3 <- stat_npa3 %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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head(stat_npa3)
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#--------
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# summary stats
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#--------
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my_summary = lf_test %>%
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group_by(timepoint, mediator) %>%
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get_summary_stats(value)
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my_summary
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my_max_df = subset(my_summary
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, select = c("mediator", "timepoint"
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#, "obesity"
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, "max"))
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head(my_max_df); head(stat_npa3)
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#-----------------------------
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# merge my_max and stat_npa3
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#-----------------------------
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head(my_max_df)
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merging_cols = intersect(names(stat_npa3), names(my_max_df)); merging_cols
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stat_npa3_v2 = merge(stat_npa3, my_max_df, by = merging_cols, all.x = T)
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stat_npa3_v2$my_y_pos = (stat_npa3_v2$max)*1.2
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stat_npa3_v2$my_y_pos
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head(stat_npa3_v2); head(stat_npa3)
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p3 = ggplot(lf_test)+ geom_boxplot(aes(x = timepoint
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, y = value
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, color = obesity))+
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scale_colour_manual(values=c("blue", "red")) +
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theme(axis.text.x = element_text(size = 15)
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, axis.text.y = element_text(size = 15
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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_blank()
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, axis.title.y = element_blank()
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, strip.text.x = element_text(size = 20,margin = margin(0.05,0,0.07,0, "cm"))
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, legend.position = "top"
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, legend.title = element_text(color = "black", size = 20)
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, legend.text = element_text(size = 15)
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, plot.subtitle = element_text(size = 20, hjust = 0.5)
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, plot.title = element_text(size = 20, hjust = 0.5)) +
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labs(title ="NPA")+
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facet_wrap(~mediator, scales = "free", nrow = 2, ncol = 2)
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#p3
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p4 = p3 + stat_pvalue_manual(stat_npa3_v2
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, y.position = "my_y_pos"
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#, y.position = 50
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, label = "{p_format} {p.signif}"
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, hide.ns=T
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, tip.length = 0)+
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scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
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p4
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#=======================================
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p3_build = ggplot_build(p3)
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p3_build$layout$panel_scales_y
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get_facet_ymax <- function (x){
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ret <- x$layout$panel_scales_y
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y_max = NULL
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for (i in 1:length(ret)){
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print(i)
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y_max_i <- max(x$layout$panel_scales_y[[i]]$range$range)
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y_max = c(y_max, y_max_i)
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}
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return(y_max)
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}
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y_max_l = get_facet_ymax(p3_build); y_max_l
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#===============================================
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# facet wrap on actual data
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pdf("boxplot_stats.pdf", width = 20, height = 15)
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#=======
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# facet
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#=======
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#--------
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# wilcox stats
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#--------
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stat_npa3 <- lf_fp_npa %>%
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group_by(timepoint, mediator) %>%
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wilcox_test(value ~ obesity, paired = F) %>%
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add_significance("p")
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stat_npa3
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stat_npa3$p_format = round(stat_npa3$p, 3)
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stat_npa3 <- stat_npa3 %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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head(stat_npa3)
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#--------
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# summary stats
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#--------
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my_summary = lf_fp_npa %>%
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group_by(timepoint, mediator) %>%
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get_summary_stats(value)
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my_summary
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my_max_df = subset(my_summary
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, select = c("mediator", "timepoint", "max"))
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head(my_max_df); head(stat_npa3)
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#-----------------------------
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# merge my_max and stat_npa3
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#-----------------------------
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head(my_max_df)
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merging_cols = intersect(names(stat_npa3), names(my_max_df)); merging_cols
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stat_npa3_v2 = merge(stat_npa3, my_max_df, by = merging_cols, all.x = T)
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stat_npa3_v2$my_y_pos = (stat_npa3_v2$max)*1.2
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stat_npa3_v2$my_y_pos
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head(stat_npa3_v2); head(stat_npa3)
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p3 = ggplot(lf_fp_npa)+ geom_boxplot(aes(x = timepoint
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, y = value
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, color = obesity))+
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scale_colour_manual(values=c("blue", "red")) +
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#scale_y_log10()+
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theme(axis.text.x = element_text(size = 15)
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, axis.text.y = element_text(size = 15
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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_blank()
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, axis.title.y = element_blank()
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, strip.text.x = element_text(size = 20, margin = margin(2,0,2,0, "cm"))
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, legend.position = "top"
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, legend.title = element_text(color = "black", size = 20)
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, legend.text = element_text(size = 15)
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, plot.subtitle = element_text(size = 20, hjust = 0.5)
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, plot.title = element_text(size = 20, hjust = 0.5)) +
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labs(title ="NPA")+
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facet_wrap(~mediator, scales = "free", nrow = 5, ncol = 7)
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#p3
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p4 = p3 + stat_pvalue_manual(stat_npa3_v2
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, y.position = "my_y_pos"
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, step.increase = 0.08
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#, y.position = 50
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, label = "{p_format} {p.signif}"
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, hide.ns=T
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, tip.length = 0) #+
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#scale_y_continuous(expand = expansion(mult = c(0.05, 0.25)))
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p4
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dev.off()
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