AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
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cd9b1ad245
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c9d7ea9fad
10 changed files with 208 additions and 128 deletions
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@ -107,6 +107,6 @@ if ( all(c1, c2, c3) ) {
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aa_pos_lig1 = NULL
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aa_pos_lig2 = NULL
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aa_pos_lig3 = NULL
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tile_map=data.frame(tile=c("ALR","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("ALR","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -104,7 +104,7 @@ cat("\n==================================================="
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, aa_pos_ca
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, "\nNo. of ligand 'CDL' binding residues:" , length(aa_pos_cdl), "\n"
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, aa_pos_cdl
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, "\nNo. of ligand 'DSL' binding residues:" , length(aa_pos_dsl), "\n"
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, "\nNo. of ligand 'DPA' binding residues:" , length(aa_pos_dsl), "\n"
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, aa_pos_dsl, "\n"
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)
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##############################################################
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@ -117,6 +117,6 @@ aa_pos_lig1 = aa_pos_dsl #slategray
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aa_pos_lig2 = aa_pos_cdl #navy blue
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aa_pos_lig3 = aa_pos_ca #purple
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tile_map=data.frame(tile=c("EMB","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("EMB","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -132,6 +132,6 @@ cat("\n==================================================="
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aa_pos_lig1 = aa_pos_rna
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aa_pos_lig2 = aa_pos_sam
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aa_pos_lig3 = aa_pos_amp
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tile_map=data.frame(tile=c("GID","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("GID","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -106,6 +106,6 @@ cat("\n==================================================="
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aa_pos_lig1 = aa_pos_hem
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aa_pos_lig2 = NULL
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aa_pos_lig3 = NULL
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tile_map=data.frame(tile=c("KAT","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("KAT","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -56,6 +56,6 @@ aa_pos_lig2 = NULL
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aa_pos_lig3 = NULL
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#aa_pos_lig2 = aa_pos_catalytic
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#aa_pos_lig3 = aa_pos_hbond
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tile_map=data.frame(tile=c("PZA","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("PZA","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -59,6 +59,6 @@ cat("\n==================================================="
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aa_pos_lig1 = NULL
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aa_pos_lig2 = NULL
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aa_pos_lig3 = NULL
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tile_map=data.frame(tile=c("RPO","DSL","CDL","Ca"),
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tile_map=data.frame(tile=c("RPO","DPA","CDL","Ca"),
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tile_colour=c("green","darkslategrey","navyblue","purple"))
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@ -36,10 +36,10 @@ ColourPalleteMulti = function(df, group, subgroup){
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bp_stability_hmap <- function(plot_df = merged_df3
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, xvar_colname = "position"
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, yvar_colname = 'duet_scaled' # Only here so that you can do function(df)
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, yvar_colname = 'avg_stability_scaled' # Only here so that you can do function(df)
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#, bar_col_colname = "group"
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, stability_colname = "duet_scaled" # Only here so that you can do function(df)
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, stability_outcome_colname = "duet_outcome" # Only here so that you can do function(df)
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, stability_colname = "avg_stability_scaled" # Only here so that you can do function(df)
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, stability_outcome_colname = "avg_stability_outcome" # Only here so that you can do function(df)
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, p_title = "DUMMY TITLE", # Only here so that you can do function(df)
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my_xaxls = 6, # x-axis label size
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my_yaxls = 6, # y-axis label size
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@ -54,15 +54,18 @@ bp_stability_hmap <- function(plot_df = merged_df3
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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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, tH0 = 0.2,
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y_max_override = 1, # an override for tidily plotting multiple different-ranged plots together
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reorder_position = FALSE # enable to reorder according to plot_df$pos_count
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)
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{
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# Custom 2: x-axis geom tiles ~ lig distance
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# order the df by position and ensure it is a factor
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# order the df by position and ensure it is a factor
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plot_df = plot_df[order(plot_df[[xvar_colname]]), ]
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plot_df[[xvar_colname]] = factor(plot_df[[xvar_colname]])
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@ -76,10 +79,18 @@ bp_stability_hmap <- function(plot_df = merged_df3
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#
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# Add col: 'group'
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plot_df$group = paste0(plot_df[[stability_outcome_colname]], "_", my_grp, sep = "")
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plot_df=plot_df %>% dplyr::add_count(position)
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plot_df$pos_count=plot_df$n
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plot_df$n=NULL
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# check unique values in normalised data
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# cat("\nNo. of unique values in", stability_colname, "no rounding:"
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# , length(unique(plot_df[[stability_colname]])))
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# define a "max Y" in case the user didn't supply one
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if(reorder_position) {
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y_max = max(plot_df$pos_count)
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}
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else{
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y_max = 1 # boring default
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}
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y_axis_limit = round_any(y_max, y_max_override, ceiling)
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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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@ -87,55 +98,63 @@ bp_stability_hmap <- function(plot_df = merged_df3
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cat("\nNo. of sub colours generated:", length(subcols_bp_hmap))
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anno_bar=position_annotation(plot_df,
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aa_pos_drug=aa_pos_drug,
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active_aa_pos=active_aa_pos,
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aa_pos_lig1=aa_pos_lig1,
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aa_pos_lig2=aa_pos_lig2,
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aa_pos_lig3=aa_pos_lig3
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reorder_position=reorder_position,
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aa_pos_drug=aa_pos_drug,
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active_aa_pos=active_aa_pos,
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aa_pos_lig1=aa_pos_lig1,
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aa_pos_lig2=aa_pos_lig2,
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aa_pos_lig3=aa_pos_lig3
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)
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# Generate the subcols barplot
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cowplot::plot_grid(
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ggplot(plot_df, aes_string(x = xvar_colname
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#, ordered = T
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)
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) +
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geom_bar(aes(fill = group)
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, colour = "grey", size=0.125) +
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scale_fill_manual( values = subcols_bp_hmap
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, guide = "none") +
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# scale_x_discrete("Position", labels=factor(plot_df$position)) +
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theme(
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panel.grid = element_line(color="lightgrey", size=0.125)
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, axis.text.x = element_text(size = my_xaxls
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subcols_plot = ggplot(plot_df) +
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scale_fill_manual( values = subcols_bp_hmap
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, guide = "none") +
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# scale_x_discrete("Position", labels=factor(plot_df$position)) +
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scale_y_continuous(limits=c(0,y_axis_limit)) +
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theme(
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panel.grid = element_line(color="lightgrey", size=0.125)
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, 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_blank()
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, axis.ticks = element_blank()
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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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# , panel.grid = element_blank()
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, panel.background = element_rect(fill = "transparent", colour=NA)
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) +
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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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, 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_blank()
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, axis.ticks = element_blank()
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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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# , panel.grid = element_blank()
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, panel.background = element_rect(fill = "transparent", colour=NA)
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) +
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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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if(reorder_position) {
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geom_bar(aes(x=reorder(position,-pos_count), fill = group),
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colour = "grey",
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size=0.125
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)
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}else{
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geom_bar(aes(x=position, fill = group),
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colour = "grey",
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size=0.125
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)
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}
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# Generate the subcols barplot
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cowplot::plot_grid(
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subcols_plot,
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NULL,
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anno_bar,
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#generate_distance_legend(plot_df),
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ncol = 1,
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align = "v",
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rel_heights = c(6,-0.1,1)
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#rel_widths = c(9/10, 0.4/10)
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)
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}
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@ -81,13 +81,11 @@ LogoPlotCustomH <- function(plot_df
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if (rm_empty_y){
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cat(paste0("Original Rows: ",nrow(plot_df)))
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plot_df = plot_df[!is.na(plot_df[y_axis_colname]),]
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cat("\nRemoving empty positions...\n")
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cat(paste0("Plotting Rows after removing NAs: ",nrow(plot_df)))
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}
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y_max = max(plot_df[[y_axis_colname]], na.rm = T)
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cat("\nRemoving y scale incremenet:", y_axis_increment)
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y_lim = round_any(y_max, y_axis_increment, f = ceiling)
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#-------------------
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# logo data: LogOR
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@ -98,8 +96,10 @@ LogoPlotCustomH <- function(plot_df
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plot_df[log_colname] = log_value(plot_df[y_axis_colname])
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logo_df = plot_df[, c(x_axis_colname, symbol_colname, log_colname)]
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logo_df_plot = logo_df[, c(x_axis_colname, symbol_colname, log_colname)]
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logo_dfP_wf = as.matrix(logo_df_plot %>% spread(x_axis_colname, log_colname, fill = 0.0))
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logo_df_plot = logo_df_plot %>% spread(x_axis_colname, y_axis_colname, fill = 0.0)
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rownames(logo_df_plot) = logo_df_plot$mutant_type
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logo_df_plot$mutant_type = NULL
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logo_dfP_wf=as.matrix(logo_df_plot)
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#!!! For consideration: to add y_axis 'breaks' and 'limits' !!!
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#y_max = max(plot_df[[log_colname]], na.rm = T)
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#y_axis_increment =
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@ -114,18 +114,28 @@ LogoPlotCustomH <- function(plot_df
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#-------------------
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logo_df = plot_df[, c(x_axis_colname, symbol_colname, y_axis_colname)]
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logo_df_plot = logo_df[, c(x_axis_colname, symbol_colname, y_axis_colname)]
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logo_dfP_wf = as.matrix(logo_df_plot %>% spread(x_axis_colname, y_axis_colname, fill = 0.0))
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logo_df_plot = logo_df_plot %>% spread(x_axis_colname, y_axis_colname, fill = 0.0)
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rownames(logo_df_plot) = logo_df_plot$mutant_type
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logo_df_plot$mutant_type = NULL
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logo_dfP_wf=as.matrix(logo_df_plot)
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#logo_dfP_wf = as.matrix(logo_df_plot %>% spread(x_axis_colname, y_axis_colname, fill = 0.0))
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}
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#class(logo_dfP_wf)
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rownames(logo_dfP_wf) = logo_dfP_wf[,1]
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#rownames(logo_dfP_wf) = logo_dfP_wf[,1]
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#dim(logo_dfP_wf)
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logo_dfP_wf = logo_dfP_wf[,-1]
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#logo_dfP_wf = logo_dfP_wf[,-1]
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#str(logo_dfP_wf)
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#y_max = max(plot_df[[y_axis_colname]], na.rm = T)
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y_max = max(colSums(logo_dfP_wf))
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cat("\nRemoving y scale incremenet:", y_axis_increment)
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y_lim = round_any(y_max, y_axis_increment, f = ceiling)
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#colnames(logo_dfP_wf)
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position_or = as.numeric(colnames(logo_dfP_wf))
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@ -167,11 +177,12 @@ LogoPlotCustomH <- function(plot_df
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ggplot() +
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geom_logo(logo_dfP_wf
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, method = "custom"
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#, method = "bits"
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, col_scheme = my_logo_col
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, seq_type = "aa") +
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#ylab("my custom height") +
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theme( axis.ticks.x = element_blank()
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, axis.ticks.length = unit(0, "pt")
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theme( axis.ticks = element_blank()
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#, axis.ticks.length = unit(0, "pt")
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, axis.title.x = element_blank()
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# , axis.text.x = element_blank() # turn this off and the below on if you want to visually
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# verify positions.
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@ -206,10 +217,13 @@ LogoPlotCustomH <- function(plot_df
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, labels = position_or
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, limits = factor(1:length(position_or))) +
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scale_y_continuous(y_lab
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, breaks = seq(0, (y_lim), by = y_axis_increment)
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#, labels = seq(0, (y_lim), by = y_axis_increment)
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, limits = c(0, y_lim)) +
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scale_y_continuous(y_lab,
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breaks = seq(0,
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(y_lim),
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by = y_axis_increment
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),
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limits = c(0, y_lim)
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) +
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labs(y=y_lab),
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position_annotation(plot_df,
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bg = theme_bgc,
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@ -3,6 +3,7 @@
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# This plots position tiles for the (up to) three ligands as well as drug
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position_annotation=function(plot_df,
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bg="transparent",
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reorder_position = FALSE, # enable to reorder according to plot_df$pos_count
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aa_pos_drug=1:100,
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active_aa_pos=1:100,
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aa_pos_lig1=1:100,
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@ -47,65 +48,112 @@ position_annotation=function(plot_df,
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plot_df$col_bg3 = ifelse(plot_df[["position"]]%in%aa_pos_lig3
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, "purple", plot_df$col_bg3)
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# the call to generate_distance_colour_map should probably be
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# wherever the outer DF is built, and not here.
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plot_df = generate_distance_colour_map(plot_df, debug=TRUE)
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heat_bar = ggplot(plot_df,
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aes(x=factor(position)) # THIS STUPID FUCKING FACTOR THING
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) +
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geom_tile(aes(y=0),
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fill=plot_df$ligD_colours) +
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heat_bar = ggplot(plot_df) + # THIS STUPID FUCKING FACTOR THING
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# scale_x_discrete("Position", labels=factor(plot_df$position)) +
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theme_nothing() +
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theme(#axis.text.x = element_text(angle = 90, size = 6),
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title = element_blank()
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) + # enable for alignment debug
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labs(x = NULL, y = NULL) #end of distance-heat-bar
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#NULL,
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pos_tiles = ggplot(plot_df,
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aes(x=factor(position), # THIS STUPID FUCKING FACTOR THING
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)
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) +
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# geom_tile(aes(y = 0, fill = col_aa, colour = col_aa)
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# ) +
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geom_tile(aes(y = 1, fill = bg_all, colour = bg_all)
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) +
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geom_tile(aes(y = 2, fill = col_bg1, colour = col_bg1)
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) +
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geom_tile(aes(y = 3, fill = col_bg2, colour = col_bg2)
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) +
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geom_tile(aes(y = 4, fill = col_bg3, colour = col_bg3)
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) +
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) + # enable for alignment debug
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labs(x = NULL, y = NULL) +
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#scale_x_discrete("Position", labels=factor(plot_df$position)) +
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scale_color_manual(values = c(
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"brown"="brown",
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"green"="#00ff00",
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"transparent"="transparent",
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"slategrey"="#2f4f4f",
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"navyblue"="#000080",
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"purple"="#a020f0"
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),
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#expand=c(0,0)
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) +
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scale_fill_manual(values = c(
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"brown"="brown",
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"green"="#00ff00",
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"transparent"="transparent",
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"slategrey"="#2f4f4f",
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"navyblue"="#000080",
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"purple"="#a020f0"
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),
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#expand=c(0,0)
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) +
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theme_nothing() +
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theme(plot.background = element_rect(fill = bg, colour=NA),
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#plot.margin = margin(t=0,b=0),
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panel.background = element_rect(fill = bg, colour=NA),
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||||
legend.position = "none"
|
||||
) +
|
||||
labs(x = NULL, y= NULL)
|
||||
|
||||
heat_legend=get_legend(heat_bar)
|
||||
# if reorder_position is turned on then we need to reorder 'x'
|
||||
# according to the pos_count column (creating this column is
|
||||
# left as a fun exercise to whoever reads this next)
|
||||
if(reorder_position) {
|
||||
geom_tile(aes(y=0, x=reorder(position,-pos_count)),
|
||||
fill=plot_df$ligD_colours)
|
||||
} else {
|
||||
geom_tile(aes(y=0, x=factor(position)),
|
||||
fill=plot_df$ligD_colours)
|
||||
}
|
||||
#end of distance-heat-bar
|
||||
#NULL,
|
||||
if(reorder_position) {
|
||||
pos_tiles = ggplot(plot_df) +
|
||||
#scale_x_discrete("Position", labels=factor(plot_df$position)) +
|
||||
scale_color_manual(values = c(
|
||||
"brown"="brown",
|
||||
"green"="#00ff00",
|
||||
"transparent"="transparent",
|
||||
"slategrey"="#2f4f4f",
|
||||
"navyblue"="#000080",
|
||||
"purple"="#a020f0"
|
||||
),
|
||||
#expand=c(0,0)
|
||||
) +
|
||||
scale_fill_manual(values = c(
|
||||
"brown"="brown",
|
||||
"green"="#00ff00",
|
||||
"transparent"="transparent",
|
||||
"slategrey"="#2f4f4f",
|
||||
"navyblue"="#000080",
|
||||
"purple"="#a020f0"
|
||||
),
|
||||
#expand=c(0,0)
|
||||
) +
|
||||
theme_nothing() +
|
||||
theme(plot.background = element_rect(fill = bg, colour=NA),
|
||||
#plot.margin = margin(t=0,b=0),
|
||||
panel.background = element_rect(fill = bg, colour=NA),
|
||||
legend.position = "none"
|
||||
) +
|
||||
labs(x = NULL, y= NULL) +
|
||||
geom_tile(aes(y = 1,x=reorder(position,-pos_count), fill = bg_all, colour = bg_all)
|
||||
) +
|
||||
geom_tile(aes(y = 2, x=reorder(position,-pos_count), fill = col_bg1, colour = col_bg1)
|
||||
) +
|
||||
geom_tile(aes(y = 3, x=reorder(position,-pos_count), fill = col_bg2, colour = col_bg2)
|
||||
) +
|
||||
geom_tile(aes(y = 4, x=reorder(position,-pos_count), fill = col_bg3, colour = col_bg3)
|
||||
)
|
||||
|
||||
} else {
|
||||
pos_tiles = ggplot(plot_df) +
|
||||
#scale_x_discrete("Position", labels=factor(plot_df$position)) +
|
||||
scale_color_manual(values = c(
|
||||
"brown"="brown",
|
||||
"green"="#00ff00",
|
||||
"transparent"="transparent",
|
||||
"slategrey"="#2f4f4f",
|
||||
"navyblue"="#000080",
|
||||
"purple"="#a020f0"
|
||||
),
|
||||
#expand=c(0,0)
|
||||
) +
|
||||
scale_fill_manual(values = c(
|
||||
"brown"="brown",
|
||||
"green"="#00ff00",
|
||||
"transparent"="transparent",
|
||||
"slategrey"="#2f4f4f",
|
||||
"navyblue"="#000080",
|
||||
"purple"="#a020f0"
|
||||
),
|
||||
#expand=c(0,0)
|
||||
) +
|
||||
theme_nothing() +
|
||||
theme(plot.background = element_rect(fill = bg, colour=NA),
|
||||
#plot.margin = margin(t=0,b=0),
|
||||
panel.background = element_rect(fill = bg, colour=NA),
|
||||
legend.position = "none"
|
||||
) +
|
||||
labs(x = NULL, y= NULL) +
|
||||
geom_tile(aes(y = 1, x=factor(position), fill = bg_all, colour = bg_all)
|
||||
) +
|
||||
geom_tile(aes(y = 2, x=factor(position), fill = col_bg1, colour = col_bg1)
|
||||
) +
|
||||
geom_tile(aes(y = 3, x=factor(position), fill = col_bg2, colour = col_bg2)
|
||||
) +
|
||||
geom_tile(aes(y = 4, x=factor(position), fill = col_bg3, colour = col_bg3)
|
||||
)
|
||||
}
|
||||
# tile thingies end
|
||||
|
||||
heat_legend=get_legend(heat_bar)
|
||||
out_plot=cowplot::plot_grid(
|
||||
heat_bar,
|
||||
NULL,
|
||||
|
|
|
|||
|
|
@ -14,9 +14,8 @@ my_gg_pairs=function(plot_df, plot_title
|
|||
title="ρ",
|
||||
digits=2,
|
||||
justify_labels = "centre",
|
||||
#title_args=c(colour="black"),
|
||||
title_args=c(size=tt_args_size),#2.5
|
||||
group_args=c(size=gp_args_size)#2.5
|
||||
title_args=list(size=tt_args_size, colour="black"),#2.5
|
||||
group_args=list(size=gp_args_size)#2.5
|
||||
)
|
||||
),
|
||||
lower = list(
|
||||
|
|
@ -93,7 +92,7 @@ corr_ps_colnames = c(static_cols
|
|||
corr_df_ps = corr_plotdf[, corr_ps_colnames]
|
||||
|
||||
# Plot #1
|
||||
plot_corr_df_ps = my_gg_pairs(corr_df_ps, plot_title="Stability features")
|
||||
plot_corr_df_ps = my_gg_pairs(corr_df_ps, plot_title="Stability estimates")
|
||||
##########################################################
|
||||
#================
|
||||
# Conservation
|
||||
|
|
@ -109,7 +108,7 @@ corr_conservation_cols = c( static_cols
|
|||
corr_df_cons = corr_plotdf[, corr_conservation_cols]
|
||||
|
||||
# Plot #2
|
||||
plot_corr_df_cons = my_gg_pairs(corr_df_cons, plot_title="Conservation features")
|
||||
plot_corr_df_cons = my_gg_pairs(corr_df_cons, plot_title="Conservation estimates")
|
||||
|
||||
##########################################################
|
||||
#================
|
||||
|
|
@ -139,7 +138,7 @@ corr_df_aff = corr_affinity_df[, corr_aff_colnames]
|
|||
colnames(corr_df_aff)
|
||||
|
||||
# Plot #3
|
||||
plot_corr_df_aff = my_gg_pairs(corr_df_aff, plot_title="Affinity features", tt_args_size = 4, gp_args_size =4)
|
||||
plot_corr_df_aff = my_gg_pairs(corr_df_aff, plot_title="Affinity estimates", tt_args_size = 4, gp_args_size =4)
|
||||
|
||||
#=============
|
||||
# combine
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue