generating plots for all sample types withoout stats
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2 changed files with 217 additions and 136 deletions
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@ -7,3 +7,5 @@ library(rstatix)
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library(Hmisc)
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library(qwraps2)
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source("legend_adjustment.R")
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# https://www.datanovia.com/en/blog/how-to-add-p-values-onto-a-grouped-ggplot-using-the-ggpubr-r-package/#perform-all-pairwise-comparisons
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329
boxplot.R
329
boxplot.R
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@ -22,137 +22,47 @@ outfile_bp = paste0("boxplots_", my_sample_type, ".pdf")
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output_boxplot = paste0(outdir_plots, outfile_bp); output_boxplot
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#===============================
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# data assignment for stats
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# data assignment for plots
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#================================
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wf = serum_wf[serum_wf$flustat == 1,]
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lf = serum_lf[serum_lf$flustat == 1,]
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lf$timepoint = paste0("t", lf$timepoint)
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#wf_fp_npa = npa_wf[npa_wf$flustat == 1,]
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lf_fp_npa = npa_lf[npa_lf$flustat == 1,]
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lf_fp_npa$timepoint = paste0("t", lf_fp_npa$timepoint)
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lf_fp_npa$timepoint = as.factor(lf_fp_npa$timepoint)
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lf_fp_npa$obesity = as.factor(lf_fp_npa$obesity)
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#==================
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# Data for plotting
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#==================
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# convert these to factor
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lf$obesity = as.factor(lf$obesity)
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lf$timepoint = as.factor(lf$timepoint)
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#wf_fp_sam = samm_wf[samm_wf$flustat == 1,]
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lf_fp_sam = sam_lf[sam_lf$flustat == 1,]
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lf_fp_sam$timepoint = paste0("t", lf_fp_sam$timepoint)
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lf_fp_sam$timepoint = as.factor(lf_fp_sam$timepoint)
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lf_fp_sam$obesity = as.factor(lf_fp_sam$obesity)
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#wf_fp_serum = serum_wf[serum_wf$flustat == 1,]
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lf_fp_serum = serum_lf[serum_lf$flustat == 1,]
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lf_fp_serum$timepoint = paste0("t", lf_fp_serum$timepoint)
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lf_fp_serum$timepoint = as.factor(lf_fp_serum$timepoint)
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lf_fp_serum$obesity = as.factor(lf_fp_serum$obesity)
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########################################################################
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my_comparisons <- list( c("0", "1") )
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########################################################################
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lf_test = lf[lf$mediator == "eotaxin",]
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str(lf_test)
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p = ggplot(lf_test, aes(x = timepoint, y = value, fill = obesity )) +
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geom_boxplot(width = 0.5)
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p
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# see default ggplot palette
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ggplot_build(p)$data
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p + stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = F
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, label = "p.format")
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########################################################################
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library(ggpubr)
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library(rstatix)
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# stats
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stat.test <- lf_test %>%
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group_by(timepoint) %>%
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wilcox_test(value ~ obesity) %>%
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adjust_pvalue(method = "bonferroni") %>%
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add_significance("p.adj")
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stat.test
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# add stats to grouped boxplots
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str(lf_test)
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lf_test$obesity = as.factor(lf_test$obesity) # ensure factor
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bxp <- ggboxplot(lf_test, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D"))
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bxp
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stat.test <- stat.test %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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bxp + stat_pvalue_manual(
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stat.test, label = "p", tip.length = 0
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)
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################################
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lf_test2 = lf[order(lf$mediator),] # 2 meds
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lf_test2 = lf_test2[1:798,]
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table(lf_test2$mediator)
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str(lf_test2)
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stat.test <- lf_test2 %>%
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group_by(timepoint, mediator) %>%
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wilcox_test(value ~ obesity, paired = F) %>%
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#adjust_pvalue(method = "bonferroni") %>%
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#add_significance("p.adj")
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add_significance("p")
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stat.test
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bxp <- ggboxplot(lf_test2, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, scales = "free_y")
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bxp
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stat.test <- stat.test %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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bxp + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
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########################################################################
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lf_comp = lf[-which(is.na(lf$value)),]
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lf_test_comp = lf_comp[lf_comp$mediator == "eotaxin",]
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str(lf_comp)
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p2 = ggplot(lf_test_comp, aes(x = timepoint, y = value, fill = obesity )) +
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geom_boxplot(width = 0.5)
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p2
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########################################################################
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# Output plots as one pdf
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cat("Output plots will be in:", output_boxplot)
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pdf(output_boxplot, width = 25, height = 15)
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#stats data
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str(lf)
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stat.test <- lf %>%
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group_by(timepoint, mediator) %>%
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wilcox_test(value ~ obesity, paired = F) %>%
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#adjust_pvalue(method = "bonferroni") %>%
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#add_significance("p.adj")
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add_significance("p")
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stat.test
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bxp <- ggboxplot(lf, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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scale_y_log10()
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bxp
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bxp + stat.test <- stat.test %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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bxp + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
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dev.off()
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######output
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# Output plots as one pdf
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cat("Output plots will be in:", output_boxplot)
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pdf(output_boxplot, width = 20, height = 15)
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my_title1 = "Boxplots: serum"
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bxp <- ggboxplot(lf, x = "timepoint", y = "value",
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#=======================================================================
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# SAM
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#=======================================================================
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if (is.factor(lf_fp_sam$timepoint) && is.factor(lf_fp_sam$timepoint)){
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cat ("PASS: required groups are factors")
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}
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table(lf_fp_sam$mediator)
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lf_fp_sam = lf_fp_sam[!lf_fp_sam$mediator == "vitd",]
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#------------------------------------------
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title_sam_linear = "Boxplot: sam (Linear)"
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#-----------------------------------------
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bxp_sam_linear <- ggboxplot(lf_fp_sam, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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scale_y_log10()
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bxp + theme(axis.text.x = element_text(size = 15)
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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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@ -164,8 +74,177 @@ bxp + theme(axis.text.x = element_text(size = 15)
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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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, legend.direction = "horizontal") +
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labs(title = my_title1
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labs(title = title_sam_linear
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, x = ""
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, y = "Levels (Log10)")
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#shift_legend2(bxp)
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, y = "Levels")
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bxp_sam_linear
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#------------------------------------
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title_sam_log = "Boxplot: sam (Log)"
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#-----------------------------------
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bxp_sam_log <- ggboxplot(lf_fp_sam, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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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_text(size = 15)
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, axis.title.y = element_text(size = 15)
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, plot.title = element_text(size = 20, hjust = 0.5)
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, strip.text.x = element_text(size = 15, colour = "black")
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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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, legend.direction = "horizontal") +
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labs(title = title_sam_log
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, x = ""
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, y = "Levels (Log)")
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bxp_sam_log
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#=======================================================================
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# SERUM
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#=======================================================================
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if (is.factor(lf_fp_serum$timepoint) && is.factor(lf_fp_serum$timepoint)){
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cat ("PASS: required groups are factors")
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}
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table(lf_fp_serum$mediator)
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#------------------------------------------
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title_serum_linear = "Boxplot: serum (Linear)"
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#-----------------------------------------
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bxp_serum_linear <- ggboxplot(lf_fp_serum, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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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_text(size = 15)
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, axis.title.y = element_text(size = 15)
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, plot.title = element_text(size = 20, hjust = 0.5)
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, strip.text.x = element_text(size = 15, colour = "black")
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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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, legend.direction = "horizontal") +
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labs(title = title_serum_linear
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, x = ""
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, y = "Levels")
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bxp_serum_linear
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#------------------------------------
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title_serum_log = "Boxplot: serum (Log)"
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#-----------------------------------
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bxp_serum_log <- ggboxplot(lf_fp_serum, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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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_text(size = 15)
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, axis.title.y = element_text(size = 15)
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, plot.title = element_text(size = 20, hjust = 0.5)
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, strip.text.x = element_text(size = 15, colour = "black")
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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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, legend.direction = "horizontal") +
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labs(title = title_serum_log
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, x = ""
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, y = "Levels (Log)")
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bxp_serum_log
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#=======================================================================
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# NPA
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#=======================================================================
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if (is.factor(lf_fp_npa$timepoint) && is.factor(lf_fp_npa$timepoint)){
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cat ("PASS: required groups are factors")
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}
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table(lf_fp_npa$mediator)
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head(lf_fp_npa$value[lf_fp_npa$mediator == "vitd"])
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lf_fp_npa = lf_fp_npa[!lf_fp_npa$mediator == "vitd",]
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#------------------------------------------
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title_npa_linear = "Boxplot: NPA (Linear)"
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#-----------------------------------------
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bxp_npa_linear <- ggboxplot(lf_fp_npa, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = T)+
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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_text(size = 15)
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, axis.title.y = element_text(size = 15)
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, plot.title = element_text(size = 20, hjust = 0.5)
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, strip.text.x = element_text(size = 15, colour = "black")
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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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, legend.direction = "horizontal") +
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labs(title = title_npa_linear
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, x = ""
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, y = "Levels")
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bxp_npa_linear
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#------------------------------------
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title_npa_log = "Boxplot: NPA (Log)"
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#-----------------------------------
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bxp_npa_log <- ggboxplot(lf_fp_npa, x = "timepoint", y = "value",
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color = "obesity", palette = c("#00BFC4", "#F8766D")) +
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facet_wrap(~mediator, nrow = 7, ncol = 5, scales = "free_y", shrink = F)+
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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_text(size = 15)
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, axis.title.y = element_text(size = 15)
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, plot.title = element_text(size = 20, hjust = 0.5)
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, strip.text.x = element_text(size = 15, colour = "black")
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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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, legend.direction = "horizontal") +
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labs(title = title_npa_log
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, x = ""
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, y = "Levels (Log)")
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bxp_npa_log
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dev.off()
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#==========================================================================
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#------------------------------------
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title_npa_log_stats = "Boxplot: NPA (Log) + stats"
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#-----------------------------------
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stat.test <- 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.test
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stat.test <- stat.test %>%
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add_xy_position(x = "timepoint", dodge = 0.8)
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bxp_npa_linear + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
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bxp_npa_log + stat_pvalue_manual(stat.test, label = "p.signif", tip.length = 0)
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dev.off()
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