265 lines
7.9 KiB
R
Executable file
265 lines
7.9 KiB
R
Executable file
#!/usr/bin/env Rscript
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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#########################################################
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# TASK: output barplot by position with each bar coloured by
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# its stability value and active site positions indicated
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# according to colour specified in "subcols_axis_PS.R"
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#########################################################
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#=======================================================================
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############################################################
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# 1: Installing and loading required packages and functions
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############################################################
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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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source("barplot_colour_function.R")
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#source("subcols_axis.R")
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source("subcols_axis.R")
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# should return the following dfs, directories and variables
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# mut_pos_cols
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# mut_pos_cols_lig
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# my_df_cols
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# my_df_u_cols
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# my_df_u_lig_cols
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# dup_muts_cols
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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(dup_muts_cols, mut_pos_cols, my_df_cols, my_df_u_cols, upos)
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#=======================================================================
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# !!! very important!!!!
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#================
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# Inspecting mut_pos_cols
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# position numbers and colours and assigning axis colours based on lab_fg
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# of the correct df
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# open file from desktop ("sample_axis_cols") for cross checking
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#================
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if ( nrow(mut_pos_cols_lig) == length(unique(my_df_u_cols_lig$position)) ){
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print("PASS: lengths checked, assigning axis colours")
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my_axis_colours = mut_pos_cols_lig$lab_fg
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cat("length of axis colours:", length(my_axis_colours)
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, "\nwhich corresponds to the number of positions on the x-axis of the plot")
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}else{
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print("FAIL:lengths mismatch, could not assign axis colours")
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quit()
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}
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# further sanity checks
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table(mut_pos_cols_lig$lab_bg)
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check_lab_bg = sum( table(mut_pos_cols_lig$lab_bg) ) == nrow(mut_pos_cols_lig) # should be True
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check_lab_bg
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table(mut_pos_cols_lig$lab_bg2)
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check_lab_bg2 = sum( table(mut_pos_cols_lig$lab_bg2) ) == nrow(mut_pos_cols_lig) # should be True
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check_lab_bg2
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table(mut_pos_cols_lig$lab_fg)
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check_lab_fg = sum( table(mut_pos_cols_lig$lab_fg) ) == nrow(mut_pos_cols_lig) # should be True
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check_lab_fg
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# sanity checks:
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if (check_lab_bg && check_lab_bg2 && check_lab_fg) {
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print("PASS: No. of assigned colours match length")
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}else{
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print("FAIL: length of assigned colours mismatch")
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quit()
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}
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#=======================================================================
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#=======
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# output
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#=======
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# plot name and location
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print(paste0("plot will be in:", plotdir))
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bp_aa_subcols_ligand = "barplot_acoloured_LIG.svg"
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plot_bp_aa_subcols_ligand = paste0(plotdir, "/", bp_aa_subcols_ligand)
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#=======================================================================
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#================
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# Data for plots
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#================
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# REASSIGNMENT as necessary
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df = my_df_u_cols_lig
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cat("ligand df dim:", dim(df))
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# sanity checks
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str(df)
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# sanity check
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df[df$position == "49",]
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df[df$position == "13",]
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df[df$position == "103",]
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###########################
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# Plot: Ligand affinity
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###########################
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#==========================
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# Barplot with scores (unordered)
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# corresponds to ligand_outcome
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# Stacked Barplot with colours: ligand_outcome @ position coloured by
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# stability scores. This is a barplot where each bar corresponds
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# to a SNP and is coloured by its corresponding ligand stability value.
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# Normalised values (range between -1 and 1 ) to aid visualisation
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# NOTE: since barplot plots discrete values, colour = score, so number of
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# colours will be equal to the no. of unique normalised scores
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# rather than a continuous scale
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# will require generating the colour scale separately.
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#============================
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# sanity checks
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upos = unique(df$position)
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table(df$ligand_outcome)
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table(df$ligand_outcome)
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# add frequency of positions (from lib data.table)
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setDT(df)[, pos_count := .N, by = .(position)]
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# this is cummulative
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table(df$pos_count)
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# use group by on this
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library(dplyr)
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snpsBYpos_df <- df %>%
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group_by(position) %>%
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summarize(snpsBYpos = mean(pos_count))
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table(snpsBYpos_df$snpsBYpos)
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snp_count = sort(unique(snpsBYpos_df$snpsBYpos))
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# sanity checks
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# should be a factor
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if (is.factor(df$ligand_outcome)){
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print("ligand_outcome is factor")
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}else{
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print("converting ligand_outcome to factor")
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df$ligand_outcome = as.factor(df$ligand_outcome)
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}
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is.factor(df$ligand_outcome)
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table(df$ligand_outcome)
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# may not be -1 and 1 since these are filtered within 10A
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min(df$affinity_scaled)
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max(df$affinity_scaled)
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# sanity checks
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# very important!!!!
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tapply(df$affinity_scaled, df$ligand_outcome, min)
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tapply(df$affinity_scaled, df$ligand_outcome, max)
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# My colour FUNCTION: based on group and subgroup
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# in my case;
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# df = df
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# group = ligand_outcome
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# subgroup = normalised score i.e affinity_scaled
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# check unique values in normalised data
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u = unique(df$affinity_scaled)
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cat("No. of unique values in normalised data:", length(u))
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# Define group
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# Create an extra column called group which contains the "gp name and score"
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# so colours can be generated for each unique values in this column
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my_grp = df$affinity_scaled
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df$group <- paste0(df$ligand_outcome, "_", my_grp, sep = "")
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# Call the function to create the palette based on the group defined above
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colours <- ColourPalleteMulti(df, "ligand_outcome", "my_grp")
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print(paste0("Colour palette generated for: ", length(colours), " colours"))
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my_title = "Ligand affinity"
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cat("No. of axis colours: ", length(my_axis_colours))
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#========================
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# plot with axis colours
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#========================
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class(df$lab_bg)
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# define cartesian coord
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my_xlim = length(unique(df$position)); my_xlim
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# axis label size
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my_xals = 18
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my_yals = 18
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# axes text size
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my_xats = 14
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my_yats = 18
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#******************
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# generate plot: with axis colours
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#******************
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print(paste0("plot name:", plot_bp_aa_subcols_ligand))
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svg(plot_bp_aa_subcols_ligand, width = 26, height = 4)
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g = ggplot(df, aes(factor(position, ordered = T)))
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OutPlot_aa_LIG = g +
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coord_cartesian(xlim = c(1, my_xlim)
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#, ylim = c(0, 6)
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, ylim = c(0, max(snp_count))
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, clip = "off") +
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geom_bar(aes(fill = group), colour = "grey") +
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scale_fill_manual(values = colours
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, guide = "none") +
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geom_tile(aes(,-0.8, width = 0.95, height = 0.85)
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, fill = df$lab_bg) +
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geom_tile(aes(,-1.2, width = 0.95, height = -0.2)
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, fill = df$lab_bg2) +
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# Here it"s important to specify that your axis goes from 1 to max number of levels
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theme(axis.text.x = element_text(size = my_xats
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, angle = 90
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, hjust = 1
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, vjust = 0.4
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, colour = my_axis_colours)
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, axis.text.y = element_text(size = my_yats
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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_xals
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#, hjust = 1
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, vjust = -0.4)
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, axis.title.y = element_text(size = my_yals )
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, axis.ticks.x = element_blank()) +
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labs(title = ""
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#title = my_title
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, x = "Position"
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, y = "Frequency")
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print(OutPlot_aa_LIG)
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dev.off()
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#!!!!!!!!!!!!!!!!
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#Warning message:
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# Vectorized input to `element_text()` is not officially supported.
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#Results may be unexpected or may change in future versions of ggplot2.
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#!!!!!!!!!!!!!!!!!
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# for sanity and good practice
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#rm(df)
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