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scripts/plotting/or_plots_combined.R
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scripts/plotting/or_plots_combined.R
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: Basic lineage barplot showing numbers
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# Output: Basic barplot with lineage samples and mut count
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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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require(cowplot)
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source("combining_dfs_plotting.R")
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# should return the following dfs, directories and variables
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# PS combined:
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# 1) merged_df2
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# 2) merged_df2_comp
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# 3) merged_df3
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# 4) merged_df3_comp
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# LIG combined:
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# 5) merged_df2_lig
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# 6) merged_df2_comp_lig
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# 7) merged_df3_lig
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# 8) merged_df3_comp_lig
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# 9) my_df_u
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# 10) my_df_u_lig
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cat(paste0("Directories imported:"
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, "\ndatadir:", datadir
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, "\nindir:", indir
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, "\noutdir:", outdir
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, "\nplotdir:", plotdir))
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cat(paste0("Variables imported:"
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, "\ndrug:", drug
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, "\ngene:", gene
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, "\ngene_match:", gene_match
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, "\nAngstrom symbol:", angstroms_symbol
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, "\nNo. of duplicated muts:", dup_muts_nu
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, "\nNA count for ORs:", na_count
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, "\nNA count in df2:", na_count_df2
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, "\nNA count in df3:", na_count_df3))
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#=========================
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#=======
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# output
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#=======
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or_combined = "or_combined_PS_LIG.svg"
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plot_or_combined = paste0(plotdir,"/", or_combined)
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#or_kin_combined = "or_kin_combined_PS_LIG.svg"
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#plot_or_kin_combined = paste0(plotdir,"/", or_kin_combined)
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#=======================================================================
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###########################
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# Data for OR and stability plots
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# you need merged_df3_comp
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# since these are matched
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# to allow pairwise corr
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###########################
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ps_df = merged_df3_comp
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lig_df = merged_df3_comp_lig
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# Ensure correct data type in columns to plot: should be TRUE
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is.numeric(ps_df$or_mychisq)
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is.numeric(lig_df$or_mychisq)
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# delete variables not required
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rm(merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig, my_df_u, my_df_u_lig)
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#%% end of section 1
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# sanity check: should be <10
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if (max(lig_df$ligand_distance) < 10){
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print ("Sanity check passed: lig data is <10Ang")
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}else{
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print ("Error: data should be filtered to be within 10Ang")
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}
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#############
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# Plots: Bubble plot
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# x = Position, Y = stability
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# size of dots = OR
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# col: stability
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#############
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#-----------------
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# Plot 1: DUET vs OR by position as geom_points
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#-------------------
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my_ats = 20 # axis text size
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my_als = 22 # axis label size
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# Spelling Correction: made redundant as already corrected at the source
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#ps_df$duet_outcome[ps_df$duet_outcome=='Stabilizing'] <- 'Stabilising'
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#ps_df$duet_outcome[ps_df$duet_outcome=='Destabilizing'] <- 'Destabilising'
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table(ps_df$duet_outcome) ; sum(table(ps_df$duet_outcome))
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g1 = ggplot(ps_df, aes(x = factor(position)
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, y = duet_scaled))
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p1 = g1 +
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geom_point(aes(col = duet_outcome
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, size = or_mychisq))+
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#, size = or_kin)) + # not good, almost like log(or)
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theme(axis.text.x = element_text(size = my_ats
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, angle = 90
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, hjust = 1
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, vjust = 0.4)
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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_als)
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, axis.title.y = element_text(size = my_als)
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, legend.text = element_text(size = my_als)
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, legend.title = element_text(size = my_als) ) +
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#, legend.key.size = unit(1, "cm")) +
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labs(title = ""
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, x = "Position"
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, y = "DUET(PS)"
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, size = "Odds Ratio"
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, colour = "DUET Outcome") +
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guides(colour = guide_legend(override.aes = list(size=4)))
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p1
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#-------------------
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# generate plot 2: Lig vs OR by position as geom_points
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#-------------------
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# Spelling Correction: made redundant as already corrected at the source
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#lig_df$ligand_outcome[lig_df$ligand_outcome=='Stabilizing'] <- 'Stabilising'
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#lig_df$ligand_outcome[lig_df$ligand_outcome=='Destabilizing'] <- 'Destabilising'
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table(lig_df$ligand_outcome)
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g2 = ggplot(lig_df, aes(x = factor(position)
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, y = affinity_scaled))
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p2 = g2 +
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geom_point(aes(col = ligand_outcome
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, size = or_mychisq))+
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#, size = or_kin)) + # not good! almost like log(or)
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theme(axis.text.x = element_text(size = my_ats
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, angle = 90
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, hjust = 1
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, vjust = 0.4)
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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_als)
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, axis.title.y = element_text(size = my_als)
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, legend.text = element_text(size = my_als)
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, legend.title = element_text(size = my_als) ) +
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#, legend.key.size = unit(1, "cm")) +
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labs(title = ""
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, x = "Position"
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, y = "Ligand Affinity"
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, size = "Odds Ratio"
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, colour = "Ligand Outcome"
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) +
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guides(colour = guide_legend(override.aes = list(size=4)))
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p2
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#======================
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# combine using cowplot
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#======================
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svg(plot_or_combined, width = 32, height = 12)
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#svg(plot_or_kin_combined, width = 32, height = 12)
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theme_set(theme_gray()) # to preserve default theme
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printFile = cowplot::plot_grid(plot_grid(p1, p2
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, ncol = 1
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, align = 'v'
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, labels = c("", "")
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, label_size = my_als+5))
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print(printFile)
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dev.off()
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