separated plotting_thesis for generating plots

scripts/plotting/plotting_thesis/linage_dist_ens_stability.R

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+#!/usr/bin/env Rscript  
+
+#########################################################
+# TASK: Lineage dist plots for stability:
+# average the four tools
+
+# func from : lineage_dist.R
+# plotdf
+# , x_axis = "duet_scaled"
+# , y_axis = "lineage_labels"
+# , x_lab = "DUET"
+# , all_lineages = F
+# , use_lineages = c("L1", "L2", "L3", "L4")
+# , with_facet = F
+# , facet_wrap_var = "" # FIXME: document what this is for
+# , fill_categ = "mutation_info_labels"
+# , fill_categ_cols = c("#E69F00", "#999999")
+# , my_ats = 15 # axis text size
+# , my_als = 20 # axis label size
+# , my_leg_ts = 16
+# , my_leg_title = 16
+# , my_strip_ts = 20
+# , leg_pos = c(0.8, 0.9)
+# , leg_pos_wf = c("top", "left", "bottom", "right")
+# , leg_dir_wf = c("horizontal", "vertical")
+# , leg_label = ""
+#########################################################
+
+#=======
+# output
+#=======
+outdir_images = paste0("~/git/Writing/thesis/images/results/"
+                       , tolower(gene), "/")
+cat("plots will output to:", outdir_images)
+#########################################################
+#=======
+# Data
+#=======
+df2 = merged_df2
+
+#==================================
+# PREFORMATTING: for consistency
+# IMPORTANT for calculating effects
+#==================================
+head(df2$ddg_foldx)
+df2['ddg_foldxC'] = abs(df2$ddg_foldx)
+head(df2['ddg_foldxC'])
+
+# reverse signs for foldx scaled values for consistency with other tools
+df2['foldx_scaled_signC'] = abs(df2$foldx_scaled)
+
+# remove the old ones from 
+rm_foldx_cols = c("ddg_foldx","foldx_scaled")
+raw_cols_stab_revised    = raw_cols_stability[!raw_cols_stability%in%rm_foldx_cols]
+raw_cols_stab_revised    = c(raw_cols_stab_revised,"ddg_foldxC")
+
+scaled_cols_stab_revised = scaled_cols_stability[!scaled_cols_stability%in%rm_foldx_cols]
+scaled_cols_stab_revised = c(scaled_cols_stab_revised, "foldx_scaled_signC")
+
+
+#=================
+# PREFORMATTING: for consistency
+#=================
+df2$sensitivity = ifelse(df2$dst_mode == 1, "R", "S")
+table(df2$sensitivity)
+
+cols_to_extract  = colnames(df2)[colnames(df2)%in%c(common_cols
+                                                    , outcome_cols_stability
+                                                    , raw_cols_stability
+                                                    , scaled_cols_stability
+                                                    , raw_cols_stab_revised
+                                                    , scaled_cols_stab_revised
+                                                    , "lineage","lineage_labels")]
+
+df2_plot = df2[, cols_to_extract]
+
+all(table(df2_plot$lineage) == table(df2_plot$lineage_labels))
+
+# find which stability cols to average: should contain revised foldx
+if ("foldx_scaled_signC"%in%colnames(df2_plot)){
+  cat("\nPASS: finding stability cols to average")
+  cols2avg_new = which(colnames(df2_plot)%in%scaled_cols_stab_revised)
+}else{
+  stop("\nAbort: Foldx column has opposing sign. Can't proceed to avergae.")
+}
+
+# ensemble average across predictors
+df2_plot['ens_stab_new'] = rowMeans(df2_plot[, cols2avg_new])
+
+head(df2_plot$position); head(df2_plot$mutationinformation)
+table(df2_plot['ens_stab_new'])
+
+# scaling average values
+df2_plot["ens_stab_new_scaled"] = lapply(df2_plot["ens_stab_new"]
+                                         , function(x) {
+                                           scales::rescale_mid(x
+                                                           , to  = c(-1,1)
+                                                           , from = c( min(df2_plot["ens_stab_new"])
+                                                                       , max(df2_plot["ens_stab_new"]))
+                                                           , mid = 0
+                                                           #, from = c(0,1))
+                                           )})
+
+min(df2_plot['ens_stab_new']); max(df2_plot['ens_stab_new'])
+foo = df2_plot[c("cols2avg_new", "ens_stab_new_scaled")]
+min(df2_plot['ens_stab_new_scaled']); max(df2_plot['ens_stab_new_scaled'])
+
+###########################################################
+#====================
+# Output Lineage plot
+#====================
+linD_ens_stabP = paste0(outdir_images
+                          , tolower(gene)
+                          ,"_linD_ens_stabP.svg")
+
+cat("\nOutput plot:", linD_ens_stabP)
+svg(linD_ens_stabP, width = 10, height = 10)
+
+linP_dm_om = lineage_distP(df2_plot
+                           , with_facet = F
+                           , x_axis = "ens_stab_new_scaled"
+                           , y_axis = "lineage_labels"
+                           , x_lab = "Average stability"
+                           #, fill_categ = "mutation_info_orig", fill_categ_cols = c("#E69F00", "#999999")
+                           , fill_categ = "sensitivity"
+                           , fill_categ_cols = c("red", "blue")
+                           , label_categories = c("Resistant", "Sensitive")
+                           , leg_label = ""
+                           , my_ats = 22 # axis text size
+                           , my_als = 22 # axis label size
+                           , my_leg_ts = 22
+                           , my_leg_title = 22
+                           , my_strip_ts = 22
+                           , alpha = 0.56
+)
+
+linP_dm_om
+dev.off()