Tanushree Tunstall
bdbc97c40a
which annoyingly throws away lots of useful data that RShiny needs for clickable plots. Also split the "flame bar" for ligand distance out into separate functions in generate_distance_colour_map.R. This can now be easily incorporated into any "wide" graph showing all positions.
139 lines
5.7 KiB
R
Executable file
139 lines
5.7 KiB
R
Executable file
#########################################################
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# 1b: Define function: coloured barplot by subgroup
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# LINK: https://stackoverflow.com/questions/49818271/stacked-barplot-with-colour-gradients-for-each-bar
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#########################################################
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source("~/git/LSHTM_analysis/scripts/functions/generate_distance_colour_map.R")
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ColourPalleteMulti = function(df, group, subgroup){
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# Find how many colour categories to create and the number of colours in each
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categories <- aggregate(as.formula(paste(subgroup, group, sep="~" ))
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, df
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, function(x) length(unique(x)))
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# return(categories) }
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category.start <- (scales::hue_pal(l = 100)(nrow(categories))) # Set the top of the colour pallete
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category.end <- (scales::hue_pal(l = 40)(nrow(categories))) # set the bottom
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#return(category.start); return(category.end)}
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# Build Colour pallette
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colours <- unlist(lapply(1:nrow(categories),
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function(i){
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colorRampPalette(colors = c(category.start[i]
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, category.end[i]))(categories[i,2])}))
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return(colours)
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}
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#########################################################################
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########################
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# Generate bp with
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# colour palette derived
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# from the data using
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# above function
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#########################
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bp_stability_hmap <- function(plotdf = merged_df3
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, xvar_colname = "position"
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, yvar_colname = 'duet_scaled' #FIXME: temp, remove
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#, bar_col_colname = "group"
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, stability_colname = "duet_scaled"
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, stability_outcome_colname = "duet_outcome"
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, p_title = "DUET" # "Protein stability (DUET)"
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, my_xaxls = 12 # x-axis label size
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, my_yaxls = 20 # y-axis label size
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, my_xaxts = 18 # x-axis text size
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, my_yaxts = 20 # y-axis text size
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, my_pts = 20 # plot-title size
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, my_xlab = "Position"
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, my_ylab = "No. of nsSNPs"
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# Custom 2: x-axis: geom tiles ~ lig distance
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#, A_xvar_lig = T
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, lig_dist_colname = LigDist_colname # from globals
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, tpos0 = 0 # 0 is a magic number that does my sensible default
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, tW0 = 1
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, tH0 = 0.2
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)
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{
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################################################
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# Custom 2: x-axis geom tiles ~ lig distance
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################################################
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#=========================
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# Build data with colours
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# ~ ligand distance
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#=========================
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plotdf = generate_distance_colour_map(plotdf, yvar_colname = stability_colname, debug=TRUE)
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# order the df by position and ensure it is a factor
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plotdf = plotdf[order(plotdf[[xvar_colname]]), ]
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plotdf[[xvar_colname]] = factor(plotdf[[xvar_colname]])
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#cat("\nSneak peak:\n")
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head(data.frame( plotdf[[xvar_colname]], plotdf[[stability_colname]] ) )
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# stability values isolated to help with generating column called: 'group'
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my_grp = plotdf[[stability_colname]]
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cat( "\nLength of nsSNPs:", length(my_grp)
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, "\nLength of unique values for nsSNPs:", length(unique(my_grp)) )
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# Add col: 'group'
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plotdf$group = paste0(plotdf[[stability_outcome_colname]], "_", my_grp, sep = "")
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# check unique values in normalised data
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cat("\nNo. of unique values in", stability_colname, "no rounding:"
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, length(unique(plotdf[[stability_colname]])))
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# Call the function to create the palette based on the group defined above
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#subcols_ps
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subcols_bp_hmap = ColourPalleteMulti(plotdf, stability_outcome_colname, stability_colname)
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cat("\nNo. of sub colours generated:", length(subcols_bp_hmap))
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#-------------------------------
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# Generate the subcols barplot
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#-------------------------------
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cowplot::plot_grid(
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ggplot(plotdf, aes_string(x = xvar_colname
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# , ordered = T)
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)) +
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geom_bar(aes(fill = group)
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, colour = "grey") +
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scale_fill_manual( values = subcols_bp_hmap
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, guide = "none") +
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theme( axis.text.x = element_text(size = my_xaxls
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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_yaxls
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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_xaxts)
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, axis.title.y = element_text(size = my_yaxts )
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, plot.title = element_text(size = my_pts
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, hjust = 0.5)) +
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geom_tile(aes(, tpos0 # heat-mapped distance tiles along the bot
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, width = tW0
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, height = tH0)
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, fill = plotdf$ligD_colours
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, colour = plotdf$ligD_colours
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, linetype = "blank") +
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labs(title = p_title
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, x = my_xlab
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, y = my_ylab),
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generate_distance_legend(plotdf, yvar_colname = stability_colname),
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ncol = 2,
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#align = "hv",
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rel_widths = c(9/10, 0.4/10)
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)
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}
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