259 lines
No EOL
9.3 KiB
R
259 lines
No EOL
9.3 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing boxplots for dr and other muts
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#########################################################
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#=======================================================================
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# working dir and loading libraries
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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source("Header_TT.R")
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#library(ggplot2)
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#library(data.table)
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#library(dplyr)
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source("other_plots_data.R")
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#=======
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# output
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#=======
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dr_other_combined = "dr_other_muts.svg"
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plot_dr_other_combined = paste0(plotdir,"/", dr_other_combined)
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dr_other_combined_labelled = "dr_other_muts_labelled.svg"
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plot_dr_other_combined_labelled = paste0(plotdir,"/", dr_other_combined_labelled)
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#dr_other_foldx = "dr_other_muts_foldx.svg"
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#plot_dr_other_foldx = paste0(plotdir,"/", dr_other_foldx)
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#point_legend = "point_legend.svg"
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#plot_point_legend = paste0(plotdir,"/", point_legend)
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########################################################################
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# end of data extraction and cleaning for plots #
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########################################################################
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#my_comparisons <- list( c(dr_muts_col, other_muts_col) )
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my_comparisons <- list( c("DM", "OM") )
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my_ats = 22 # axis text size
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my_als = 20 # axis label size
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my_fls = 20 # facet label size
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my_pts = 22 # plot title size
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##########################################################################
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#===========
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# Plot1: PS
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#===========
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# my_stat_ps = compare_means(param_value~mutation_info
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# , group.by = "param_type"
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# , data = df_lf_ps
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# , paired = FALSE
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# , p.adjust.method = "BH")
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y_value = "param_value"
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p1 = ggplot(lf_duet, aes(x = mutation_info
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, y = eval(parse(text=y_value)) )) +
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facet_wrap(~ param_type
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, nrow = 1
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, scales = "free_y") +
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geom_boxplot(fill = "white", outlier.colour = NA
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#, position = position_dodge(width = 0.9)
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, width = 0.2) +
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geom_point(position = position_jitterdodge(dodge.width=0.01)
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, alpha = 0.5
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, show.legend = FALSE
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, aes(colour = duet_outcome)) +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats
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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 = my_ats)
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, axis.title.y = element_text(size = my_ats)
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, plot.title = element_text(size = my_pts , hjust = 0.5, colour = "black", face = "bold")
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, strip.background = element_rect(fill = "khaki2")
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, strip.text.x = element_text(size = my_fls, colour = "black")
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, legend.title = element_text(color = "black", size = my_als)
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, legend.text = element_text(size = my_ats)
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, legend.direction = "vertical") +
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labs(title = "DUET"
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, x = ""
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, y = "")+
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stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = FALSE
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#, label = "p.format")
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, label = "p.signif")
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p1
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##########################################################################
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#=================
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# Plot 2: Foldx
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#=================
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my_stat_foldx = compare_means(param_value~mutation_info, group.by = "param_type"
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, data = df_lf_foldx, paired = FALSE, p.adjust.method = "BH")
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y_value = "param_value"
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p2 = ggplot(df_lf_foldx, aes(x = mutation_info
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, y = eval(parse(text=y_value)) )) +
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facet_wrap(~ param_type
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, nrow = 1
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, scales = "free_y") +
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geom_boxplot(fill = "white", outlier.colour = NA
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#, position = position_dodge(width = 0.2)
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, width = 0.5) +
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geom_point(position = position_jitterdodge(dodge.width=0.01)
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, alpha = 0.5
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, show.legend = FALSE
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, aes(colour = factor(foldx_outcome))) +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats
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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 = my_ats)
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, axis.title.y = element_text(size = my_ats)
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, plot.title = element_text(size = my_pts , hjust = 0.5, colour = "black", face = "bold")
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, strip.background = element_rect(fill = "palegreen1")
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, strip.text.x = element_text(size = my_fls, colour = "black")
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, legend.title = element_text(color = "black", size = my_als)
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, legend.text = element_text(size = my_ats)
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#, legend.title = element_blank()
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, legend.direction = "vertical") +
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labs(title = "Foldx"
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, x = ""
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, y = "") +
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stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = FALSE
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#, label = "p.format")
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, label = "p.signif")
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p2
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##########################################################################
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#==============
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# Plot 3: LIG
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#==============
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my_stat_lig = compare_means(param_value~mutation_info, group.by = "param_type"
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, data = df_lf_lig, paired = FALSE, p.adjust.method = "BH")
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y_value = "param_value"
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p3 = ggplot(df_lf_lig, aes(x = mutation_info
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, y = eval(parse(text=y_value)) )) +
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facet_wrap(~ param_type
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, nrow = 1
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, scales = "free_y") +
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geom_boxplot(fill = "white", outlier.colour = NA
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#, position = position_dodge(width = 0.9)
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, width = 0.2) +
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geom_point(position = position_jitterdodge(dodge.width=0.01)
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, alpha = 0.5
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, show.legend = FALSE
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, aes(colour = factor(ligand_outcome))) +
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theme(axis.text.x = element_text(size = my_ats)
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, axis.text.y = element_text(size = my_ats
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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 = my_ats)
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, axis.title.y = element_text(size = my_ats)
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, plot.title = element_text(size = my_pts , hjust = 0.5, colour = "black", face = "bold")
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, strip.background = element_rect(fill = "thistle3")
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, strip.text.x = element_text(size = my_fls, colour = "black")
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, legend.title = element_text(color = "black", size = my_als)
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, legend.text = element_text(size = my_ats)
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, legend.direction = "vertical") +
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labs(title = "Ligand Affinity"
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, x = ""
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, y = "")+
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stat_compare_means(comparisons = my_comparisons
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, method = "wilcox.test"
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, paired = FALSE
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#, label = "p.format")
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, label = "p.signif")
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p3
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##########################################################################
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#===========
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# legend
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#===========
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legend = ggplot(df_lf_foldx, aes(x = mutation_info
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, y = eval(parse(text=y_value)) )) +
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facet_wrap(~ param_type
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, nrow = 1
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, scales = "free_y") +
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geom_boxplot(fill = "white", outlier.colour = NA
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#, position = position_dodge(width = 0.2)
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, width = 0.5) +
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geom_point(position = position_jitterdodge(dodge.width=0.01)
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, aes(colour = factor(foldx_outcome))) +
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theme(legend.text = element_text(size = 25)
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, legend.direction = "vertical"
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, legend.title = element_blank()
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#, axis.text.y = element_text(size = 30, colour = "black", angle = 90)
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#, axis.text.x = element_text(size = 30, colour = "black", angle = 0)
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#, strip.background = element_rect(fill="orange")
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) +
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guides(color = guide_legend(override.aes = list(size = 6)))
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legend
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##########################################################################
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#===========================
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# combine
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#===========================
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#---------
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# plot 1
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#---------
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cat("Output plot:",plot_dr_other_combined)
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svg(plot_dr_other_combined, width = 24, height = 12)
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#theme_set(theme_gray()) # to preserve default theme
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# first combine fold and lig plots (2 and 3)
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c1 = cowplot::plot_grid(p2, p3
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#, labels = c("(b)", "(c)")
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, labels = c("B", "C")
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, hjust = -2
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, label_size = 25
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, nrow = 1
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, rel_widths = c(1/6, 5/6))
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c1
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OutPlot = cowplot::plot_grid(p1, c1
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, nrow = 2)
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print(OutPlot)
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dev.off()
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#==========================================
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# labelled
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cat("Output plot:", plot_dr_other_combined_labelled)
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svg(plot_dr_other_combined_labelled, width = 24, height = 12)
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plot_dr_other_combined_labelled
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Outplot_labelled = cowplot::plot_grid(p1, c1
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, nrow = 2
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#, labels = c("(a)", "", "")
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, labels = c("A", "", "")
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, hjust = -2
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#, vjust = 0
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, label_size = 25)
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print(Outplot_labelled)
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dev.off()
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#---------
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# plot 3: legend
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#---------
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#svg(plot_point_legend, width = 6, height = 7)
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#OutPlot3 = legend
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#print(OutPlot3)
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#dev.off() |