renamed file to reflect sucols_axis is commons script sourced by ps and lig plots
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#########################################################
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# TASK: Adding colours to dfs so they can be used for plotting
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# add cols to each of the my_df* dfs
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#########################################################
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#=======================================================================
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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("plotting_data.R")
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# should return the following dfs and directories
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# my_df
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# my_df_u
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# my_df_u_lig
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# dup_muts
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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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, "\nLength of upos:", length(upos)
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, "\nAngstrom symbol:", angstroms_symbol))
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# clear excess variable
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rm(upos, dup_muts, my_df_u, my_df_u_lig)
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# This is because we want to assign the colours to my_df
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# and then resubset accordingly for our plots to avoid multiple merges
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#=======================================================================
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# df to use: my_df
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# NOTE: my_df contains duplicate muts but its ok as you are only adding
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# colours to positions
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# sanity checks: ensure my_df is ordered by position: it should be
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my_df$position; my_df$mutationinformation
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my_df_o = my_df[order(my_df$position),]
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my_df_o$position; my_df_o$mutationinformation
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head(my_df_o$position) == head(my_df$position)
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head(my_df_o$mutationinformation) == head(my_df$mutationinformation)
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tail(my_df_o$position) == tail(my_df$position)
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tail(my_df_o$mutationinformation) == tail(my_df$mutationinformation)
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my_df = my_df_o
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# create a new df with unique position numbers and cols
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position = unique(my_df$position)
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position_cols = as.data.frame(position)
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head(position_cols) ; tail(position_cols)
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# specify active site residues and bg colour
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position = c(49, 51, 57, 71
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, 8, 96, 138
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, 13, 68
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, 103, 137
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, 133, 134) #13
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lab_bg = rep(c("purple"
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, "yellow"
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, "cornflowerblue"
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, "blue"
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, "green"), times = c(4, 3, 2, 2, 2)
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)
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# second bg colour for active site residues
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#lab_bg2 = rep(c("white"
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# , "green" , "white", "green"
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# , "white"
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# , "white"
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# , "white"), times = c(4
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# , 1, 1, 1
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# , 2
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# , 2
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# , 2)
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#)
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#%%%%%%%%%
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# revised: leave the second box coloured as the first one incase there is no second colour
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#%%%%%%%%%
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lab_bg2 = rep(c("purple"
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, "green", "yellow", "green"
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, "cornflowerblue"
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, "blue"
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, "green"), times = c(4
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, 1, 1, 1
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, 2
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, 2
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, 2))
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# fg colour for labels for active site residues
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lab_fg = rep(c("white"
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, "black"
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, "black"
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, "white"
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, "black"), times = c(4, 3, 2, 2, 2))
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#%%%%%%%%%
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# revised: make the purple ones black
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# fg colour for labels for active site residues
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#%%%%%%%%%
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#lab_fg = rep(c("black"
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# , "black"
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# , "black"
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# , "white"
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# , "black"), times = c(4, 3, 2, 2, 2))
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# combined df with active sites, bg and fg colours
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aa_cols_ref = data.frame(position
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, lab_bg
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, lab_bg2
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, lab_fg
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, stringsAsFactors = F) #13, 4
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str(position_cols); class(position_cols)
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str(aa_cols_ref); class(aa_cols_ref)
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# since position is int and numeric in the two dfs resp,
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# converting numeric to int for consistency
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aa_cols_ref$position = as.integer(aa_cols_ref$position)
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class(aa_cols_ref$position)
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#===========
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# Merge 1: merging positions df (position_cols) and
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# active site cols (aa_cols_ref)
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# linking column: "position"
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# This is so you can have colours defined for all positions
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#===========
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head(position_cols$position); head(aa_cols_ref$position)
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mut_pos_cols = merge(position_cols, aa_cols_ref
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, by = "position"
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, all.x = TRUE)
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head(mut_pos_cols)
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# replace NA"s
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# :column "lab_bg" with "white"
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# : column "lab_fg" with "black"
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mut_pos_cols$lab_bg[is.na(mut_pos_cols$lab_bg)] <- "white"
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mut_pos_cols$lab_bg2[is.na(mut_pos_cols$lab_bg2)] <- "white"
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mut_pos_cols$lab_fg[is.na(mut_pos_cols$lab_fg)] <- "black"
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head(mut_pos_cols)
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#===========
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# Merge 2: Merge mut_pos_cols with mcsm df
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# Now combined the positions with aa colours with
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# the mcsm_data
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#===========
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# dfs to merge
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df0 = my_df # my_df_o
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df1 = mut_pos_cols
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# check the column on which merge will be performed
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head(df0$position); tail(df0$position)
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head(df1$position); tail(df1$position)
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# should now have 3 extra columns
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my_df_cols = merge(df0, df1
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, by = "position"
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, all.x = TRUE)
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# sanity check
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my_df_cols[my_df_cols$position == "49",]
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my_df_cols[my_df_cols$position == "13",]
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###########################
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# extract unique mutation entries
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###########################
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# check for duplicate mutations
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if ( length(unique(my_df_cols$mutationinformation)) != length(my_df_cols$mutationinformation)){
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cat(paste0("\nCAUTION:", " Duplicate mutations identified"
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, "\nExtracting these..."))
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dup_muts_cols = my_df_cols[duplicated(my_df_cols$mutationinformation),]
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dup_muts_cols_nu = length(unique(dup_muts_cols$mutationinformation))
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cat(paste0("\nDim of duplicate mutation df:", nrow(dup_muts_cols)
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, "\nNo. of unique duplicate mutations:", dup_muts_cols_nu
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, "\n\nExtracting df with unique mutations only"))
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my_df_u_cols = my_df_cols[!duplicated(my_df_cols$mutationinformation),]
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}else{
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cat(paste0("\nNo duplicate mutations detected"))
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my_df_u_cols = my_df_cols
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}
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upos = unique(my_df_u_cols$position)
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cat("\nDim of clean df:"); cat(dim(my_df_u_cols))
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cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
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# sanity check
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my_df_u_cols[my_df_u_cols$position == "49",]
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my_df_u_cols[my_df_u_cols$position == "13",]
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my_df_u_cols[my_df_u_cols$position == "103",]
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###########################
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# extract mutations <10Angstroms
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###########################
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table(my_df_u_cols$ligand_distance<10)
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my_df_u_cols_lig = my_df_u_cols[my_df_u_cols$ligand_distance <10,]
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angstroms_symbol = "\u212b"
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cat(paste0("There are ", nrow(my_df_u_cols_lig), " sites lying within 10", angstroms_symbol, " of the ligand"))
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#=================
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# very important!
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#=================
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#my_axis_colours = mut_pos_cols$lab_fg # doesn't work if positions numbers are subsetted as in ligand
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# need the equivalent of the mut_pos_cols for ligand
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# get position numbers for ligand
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lig_pos = my_df_u_cols_lig$position
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# subset mut_pos_cols for ligand positions
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mut_pos_cols_lig = mut_pos_cols[mut_pos_cols$position %in% lig_pos,]
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#my_axis_colours = mut_pos_cols_lig$lab_fg
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#====================================================================
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# clear variables
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rm(aa_cols_ref
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, my_df
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, df0
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, df1
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, position_cols
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, lab_bg
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, lab_bg2
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, lab_fg
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, position)
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#######################################################################
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# end of script
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#######################################################################
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