reran plots with current lig dist

scripts/plotting/barplots_subcolours.R

@@ -28,8 +28,6 @@ if(is.null(drug)|is.null(gene)) {
 #===========
 # Input
 #===========
-source("../functions/bp_subcolours.R")
-
 source("get_plotting_dfs.R")
 
 #===========
@@ -44,58 +42,10 @@ bp_subcols_lig = "barplot_coloured_LIG.svg"
 plot_bp_subcols_lig = paste0(plotdir, "/", bp_subcols_lig)
 
 ##############################################################################
-#====================
+#********************
-# Data for plots: PS
+# generate plot: PS
-#====================
+# NO axis colours
-# sanity checks
+#********************
-str(my_df_u)
-upos = unique(my_df_u$position)
-
-# should be a factor
-if (is.factor(my_df_u$duet_outcome)){
-  print("duet_outcome is factor")
-}else{
-  print("convert duet_outcome to factor")
-  my_df_u$duet_outcome = as.factor(my_df_u$duet_outcome)
-}
-
-is.factor(my_df_u$duet_outcome)
-table(my_df_u$duet_outcome)
-
-# should be -1 and 1
-min(my_df_u$duet_scaled)
-max(my_df_u$duet_scaled)
-
-tapply(my_df_u$duet_scaled, my_df_u$duet_outcome, min)
-tapply(my_df_u$duet_scaled, my_df_u$duet_outcome, max)
-
-#=======================================================
-# Barplot (unordered) colour each nsSNP by stability
-## My colour FUNCTION: based on group and subgroup
-# in my case;
-# df = df
-# group = duet_outcome
-# subgroup = normalised score i.e duet_scaled
-#========================================================
-# check unique values in normalised data
-u = unique(my_df_u$duet_scaled) 
-my_grp = my_df_u$duet_scaled    #no rounding
-
-#-------------------------------------------------
-# Run this section if rounding is to be used
-#n = 3 
-#my_df_u$duet_scaledR = round(my_df_u$duet_scaled, n)
-#ur = unique(my_df_u$duet_scaledR)
-#my_grp = my_df_u$duet_scaledR  # rounding
-#---------------------------------------------------
-
-my_df_u$group <- paste0(my_df_u$duet_outcome, "_", my_grp, sep = "")
-
-# Call the function to create the palette based on the group defined above
-colours <- ColourPalleteMulti(my_df_u, "duet_outcome", "my_grp")
-print(paste0("Colour palette generated for: ", length(colours), " colours"))
-
-
 # axis label size
 my_xaxls = 12
 my_yaxls = 20
@@ -104,18 +54,15 @@ my_yaxls = 20
 my_xaxts = 18
 my_yaxts = 20
 
-my_title = "Protein stability (DUET)"
+title_ps = "Protein stability (DUET)"
-#********************
+
-# generate plot: PS
-# NO axis colours
-#********************
 print(paste0("plot name:", plot_bp_subcols_duet))
 svg(plot_bp_subcols_duet, width = 26, height = 4)
 
-g = ggplot(my_df_u, aes(factor(position, ordered = T)))
+g = ggplot(subcols_df_ps, aes(factor(position, ordered = T)))
 outPlot_bp_ps = g + 
   geom_bar(aes(fill = group), colour = "grey") +
-  scale_fill_manual( values = colours
+  scale_fill_manual( values = subcols_ps
                      , guide = "none") +
   theme( axis.text.x = element_text(size = my_xaxls
                                     , angle = 90
@@ -128,7 +75,7 @@ outPlot_bp_ps = g +
          , axis.title.x = element_text(size = my_xaxts)
          , axis.title.y = element_text(size = my_yaxts ) ) +
   labs(title = ""
-       #title = my_title
+       #title = title_ps
        , x = "Position"
        , y = "Frequency")
 
@@ -136,66 +83,10 @@ print(outPlot_bp_ps)
 dev.off()
 
 ####################################################
-#====================
+#******************
-# Data for plots: LIG
+# generate plot: LIG 
-#====================
+# NO axis colours
-# sanity checks
+#******************
-str(my_df_u_lig)
-upos = unique(my_df_u_lig$position)
-
-# should be a factor
-if (is.factor(my_df_u_lig$ligand_outcome)){
-  print("ligand_outcome is factor")
-}else{
-  print("convert ligand_outcome to factor")
-  my_df_u_lig$ligand_outcome = as.factor(my_df_u_lig$ligand_outcome)
-}
-
-is.factor(my_df_u_lig$ligand_outcome)
-table(my_df_u_lig$ligand_outcome)
-
-# should be -1 and 1
-min(my_df_u_lig$affinity_scaled)
-max(my_df_u_lig$affinity_scaled)
-
-tapply(my_df_u_lig$affinity_scaled, my_df_u_lig$ligand_outcome, min)
-tapply(my_df_u_lig$affinity_scaled, my_df_u_lig$ligand_outcome, max)
-
-#=======================================================
-# Barplot (unordered) colour each nsSNP by stability
-## My colour FUNCTION: based on group and subgroup
-# in my case;
-# df = my_df_u_lig
-# group = ligand_outcome
-# subgroup = normalised score i.e affinity_scaled
-#========================================================
-# check unique values in normalised data
-u_lig = unique(my_df_u_lig$affinity_scaled) 
-my_grp_lig = my_df_u_lig$affinity_scaled    #no rounding
-
-#-------------------------------------------------
-# Run this section if rounding is to be used
-#n = 3 
-#my_df_u_lig$affinity_scaledR = round(my_df_u_lig$affinity_scaled, n)
-#ur_lig = unique(my_df_u_lig$affinity_scaledR)
-#my_grp_lig = my_df_u_lig$affinity_scaledR  # rounding
-#---------------------------------------------------
-
-my_df_u_lig$group_lig <- paste0(my_df_u_lig$ligand_outcome, "_"
-                                , my_grp_lig
-                                , sep = "")
-
-# Call the function to create the palette based on the group defined above
-colours_lig <- ColourPalleteMulti(my_df_u_lig
-                                  , "ligand_outcome"
-                                  , "my_grp_lig")
-
-print(paste0("Colour palette generated for: "
-             , length(colours_lig)
-             , " colours_lig"))
-
-my_title_lig = "Ligand Affinity"
-
 # axis label size
 my_xaxls = 12
 my_yaxls = 20
@@ -204,17 +95,15 @@ my_yaxls = 20
 my_xaxts = 18
 my_yaxts = 20
 
-#******************
+title_lig = "Ligand Affinity"
-# generate plot: LIG 
+
-# NO axis colours
-#******************
 print(paste0("plot name:", plot_bp_subcols_lig))
 svg(plot_bp_subcols_lig, width = 26, height = 4)
 
-g2 = ggplot(my_df_u_lig, aes(factor(position, ordered = T)))
+g2 = ggplot(subcols_df_lig, aes(factor(position, ordered = T)))
 outPlot_bp_lig = g2 + 
   geom_bar(aes(fill = group_lig), colour = "grey") +
-  scale_fill_manual( values = colours_lig
+  scale_fill_manual( values = subcols_lig
                      , guide = "none") +
   theme( axis.text.x = element_text(size = my_xaxls
                                     , angle = 90
@@ -227,7 +116,7 @@ outPlot_bp_lig = g2 +
          , axis.title.x = element_text(size = my_xaxts)
          , axis.title.y = element_text(size = my_yaxts ) ) +
   labs(title = ""
-       #title = my_title_lig
+       #title = title_lig
        , x = "Position"
        , y = "Frequency")
 
@@ -235,4 +124,4 @@ print(outPlot_bp_lig)
 dev.off()
 ######################################################################=
 #                             End of script
-######################################################################=
+######################################################################=

scripts/plotting/get_plotting_dfs.R

@@ -39,8 +39,8 @@ import_dirs(drug, gene)
 #---------------------------
 # call: plotting_data()
 #---------------------------
-if (!exists("infile_params") && exists("gene")){
+#if (!exists("infile_params") && exists("gene")){
-#if (!is.character(infile_params) && exists("gene")){ # when running as cmd
+if (!is.character(infile_params) && exists("gene")){ # when running as cmd
   #in_filename_params = paste0(tolower(gene), "_all_params.csv") 
   in_filename_params = paste0(tolower(gene), "_comb_afor.csv") # part combined for gid
   infile_params = paste0(outdir, "/", in_filename_params)
@@ -62,8 +62,8 @@ dup_muts    = pd_df[[4]]
 #--------------------------------
 # call: combining_dfs_plotting()
 #--------------------------------
-if (!exists("infile_metadata") && exists("gene")){
+#if (!exists("infile_metadata") && exists("gene")){
-#if (!is.character(infile_metadata) && exists("gene")){ # when running as cmd
+if (!is.character(infile_metadata) && exists("gene")){ # when running as cmd
   in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
   infile_metadata = paste0(outdir, "/", in_filename_metadata)
   cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
@@ -95,19 +95,19 @@ merged_df3_comp_lig = all_plot_dfs[[8]]
 ####################################################################
 # can include: mutation, or_kin, pwald, af_kin
 cols_to_select = c("mutationinformation", "drtype"
-                   #, "wild_type"
+                   , "wild_type"
                    , "position"
-                   #, "mutant_type"
+                   , "mutant_type"
                    , "chain", "ligand_id", "ligand_distance"
                    , "duet_stability_change", "duet_outcome", "duet_scaled"
                    , "ligand_affinity_change", "ligand_outcome", "affinity_scaled"
                    , "ddg", "foldx_scaled", "foldx_outcome"
                    , "deepddg", "deepddg_outcome"
-                   , "asa", "rsa", "rd_values", "kd_values")
+                   , "asa", "rsa", "rd_values", "kd_values"
-                   #, "af", "or_mychisq", "pval_fisher" 
+                   , "af", "or_mychisq", "pval_fisher" 
-                   #, "or_fisher", "or_logistic", "pval_logistic")
+                   , "or_fisher", "or_logistic", "pval_logistic"
-                   #, "wt_prop_water", "mut_prop_water", "wt_prop_polarity", "mut_prop_polarity"
+                   , "wt_prop_water", "mut_prop_water", "wt_prop_polarity", "mut_prop_polarity"
-                   #, "wt_calcprop", "mut_calcprop")
+                   , "wt_calcprop", "mut_calcprop")
 
 #=======================
 # Data for sub colours