From 6934faca1093fc56370e90bdeb0c1885aaffc39c Mon Sep 17 00:00:00 2001
From: Tanushree Tunstall <tanu@tunstall.in>
Date: Thu, 10 Sep 2020 17:53:49 +0100
Subject: [PATCH] saving other_plots.R

---
 scripts/plotting/combining_dfs_plotting.R |   3 +-
 scripts/plotting/notes                    |  10 +
 scripts/plotting/other_plots.R            | 214 ++++++++++++++--------
 scripts/plotting/other_plots_data.R       | 145 ++++++++-------
 scripts/plotting/test.R                   |  96 ----------
 5 files changed, 227 insertions(+), 241 deletions(-)
 delete mode 100644 scripts/plotting/test.R

diff --git a/scripts/plotting/combining_dfs_plotting.R b/scripts/plotting/combining_dfs_plotting.R
index 911b0f8..f2589d1 100644
--- a/scripts/plotting/combining_dfs_plotting.R
+++ b/scripts/plotting/combining_dfs_plotting.R
@@ -319,8 +319,7 @@ all.equal(foo, bar)
 # clear variables
 rm(foo, bar, gene_metadata
    , in_filename_params, infile_params, merging_cols
-   , in_filename_gene_metadata, infile_gene_metadata
-   , merged_df2v2, merged_df2v3)
+   , in_filename_gene_metadata, infile_gene_metadata)
 #*************************
 #####################################################################
 #                       Combining: LIG
diff --git a/scripts/plotting/notes b/scripts/plotting/notes
index 7cc9e0e..5cbe303 100644
--- a/scripts/plotting/notes
+++ b/scripts/plotting/notes
@@ -64,3 +64,13 @@ table(snpsBYpos_df$snpsBYpos)
                          # with dups
                           1  2  3  4  5  6  7 
                           39 30 25 23 20  6  2 
+                          
+                          
+                          
+#======================
+# dr and other muts count = PS
+#======================   
+dr_mutations_pyrazinamide : 227  
+other_mutations_pyrazinamide : 197 
+                                                 
+                      
diff --git a/scripts/plotting/other_plots.R b/scripts/plotting/other_plots.R
index 2ca3868..25e0171 100644
--- a/scripts/plotting/other_plots.R
+++ b/scripts/plotting/other_plots.R
@@ -18,19 +18,29 @@ source("other_plots_data.R")
 #=======
 # output
 #=======
-dr_other_plots_combined = "dr_other_muts.svg"
-plot_dr_other_plots_combined  =  paste0(plotdir,"/", dr_other_plots_combined)
+dr_other_combined = "dr_other_muts.svg"
+plot_dr_other_combined  =  paste0(plotdir,"/", dr_other_combined)
 
+dr_other_foldx = "dr_other_muts_foldx.svg"
+plot_dr_other_foldx  =  paste0(plotdir,"/", dr_other_foldx)
+
+point_legend = "point_legend.svg"
+plot_point_legend  =  paste0(plotdir,"/", point_legend)
 ########################################################################
 #               end of data extraction and cleaning for plots          #
 ########################################################################
 #my_comparisons <- list( c(dr_muts_col, other_muts_col) )
 my_comparisons <- list( c("DM", "OM") )
 
+
+my_ats =  15# axis text size
+my_als = 20 # axis label size
+my_fls = 20 # facet label size
+my_pts = 22 # plot title size
+
 #===========
 # Plot1: PS
 #===========
-
 my_stat_ps = compare_means(param_value~mutation_info, group.by = "param_type"
                         , data = df_lf_ps,  paired = FALSE, p.adjust.method = "BH")
 
@@ -42,22 +52,23 @@ p1 = ggplot(df_lf_ps, aes(x = mutation_info
              , nrow = 1
              , scales = "free_y") + 
   geom_boxplot(fill = "white", outlier.colour = NA
-               # position = position_dodge(width = 0.9)
-               , width = 0.5) +
+               #, position = position_dodge(width = 0.9)
+               , width = 0.2) +
   geom_point(position = position_jitterdodge(dodge.width=0.01)
+             , alpha = 0.5
              , show.legend = FALSE
              , aes(colour = factor(duet_outcome))) +
-  theme(axis.text.x = element_text(size = 15)
-        , axis.text.y = element_text(size = 15
+  theme(axis.text.x = element_text(size = my_ats)
+        , axis.text.y = element_text(size = my_ats
                                      , angle = 0
                                      , hjust = 1
                                      , vjust = 0)
-        , axis.title.x = element_text(size = 15)
-        , axis.title.y = element_text(size = 15)
-        , plot.title = element_text(size = 20, hjust = 0.5)
-        , strip.text.x = element_text(size = 15, colour = "black")
-        , legend.title = element_text(color = "black", size = 20)
-        , legend.text = element_text(size = 15)
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_text(size = my_ats)
+        , plot.title = element_text(size = my_pts , hjust = 0.5)
+        , strip.text.x = element_text(size = my_fls, colour = "black")
+        , legend.title = element_text(color = "black", size = my_als)
+        , legend.text = element_text(size = my_ats)
         , legend.direction = "vertical") +
   labs(title = "DUET"
        , x = ""
@@ -68,51 +79,9 @@ p1 = ggplot(df_lf_ps, aes(x = mutation_info
                      #, label = "p.format")
                      , label = "p.signif")
 p1
-
+#===============================================================
 #===========
-# Plot 2: Foldx
-#===========
-my_stat_foldx = compare_means(param_value~mutation_info, group.by = "param_type"
-                              , data = df_lf_foldx,  paired = FALSE, p.adjust.method = "BH")
-
-y_value = "param_value"
-
-p2 = ggplot(df_lf_foldx, aes(x = mutation_info
-                             , y = eval(parse(text=y_value)) ))  + 
-  facet_wrap(~ param_type
-             , nrow = 1
-             , scales = "free_y") + 
-  geom_boxplot(fill = "white", outlier.colour = NA
-               # position = position_dodge(width = 0.9)
-               , width = 0.5) +
-  geom_point(position = position_jitterdodge(dodge.width=0.01)
-             , show.legend = FALSE
-             , aes(colour = factor(foldx_outcome))) +
-  theme(axis.text.x = element_text(size = 15)
-        , axis.text.y = element_text(size = 15
-                                     , angle = 0
-                                     , hjust = 1
-                                     , vjust = 0)
-        , axis.title.x = element_text(size = 15)
-        , axis.title.y = element_text(size = 15)
-        , plot.title = element_text(size = 20, hjust = 0.5)
-        , strip.text.x = element_text(size = 15, colour = "black")
-        , legend.title = element_text(color = "black", size = 20)
-        , legend.text = element_text(size = 15)
-        , legend.direction = "vertical") +
-  labs(title = "Foldx"
-       , x = ""
-       , y = "")+ 
-  stat_compare_means(comparisons = my_comparisons
-                     , method = "wilcox.test"
-                     , paired = FALSE
-                     #, label = "p.format")
-                     , label = "p.signif")
-p2
-
-
-#===========
-# Plot 3: LIG
+# Plot 2: LIG
 #===========
 
 my_stat_lig = compare_means(param_value~mutation_info, group.by = "param_type"
@@ -120,28 +89,29 @@ my_stat_lig = compare_means(param_value~mutation_info, group.by = "param_type"
 
 y_value = "param_value"
 
-p3 = ggplot(df_lf_lig, aes(x = mutation_info
+p2 = ggplot(df_lf_lig, aes(x = mutation_info
                            , y = eval(parse(text=y_value)) ))  + 
   facet_wrap(~ param_type
              , nrow = 1
              , scales = "free_y") + 
   geom_boxplot(fill = "white", outlier.colour = NA
-               # position = position_dodge(width = 0.9)
-               , width = 0.5) +
+               #, position = position_dodge(width = 0.9)
+               , width = 0.2) +
   geom_point(position = position_jitterdodge(dodge.width=0.01)
+             , alpha = 0.5
              , show.legend = FALSE
              , aes(colour = factor(ligand_outcome))) +
-  theme(axis.text.x = element_text(size = 15)
-        , axis.text.y = element_text(size = 15
+  theme(axis.text.x = element_text(size = my_ats)
+        , axis.text.y = element_text(size = my_ats
                                      , angle = 0
                                      , hjust = 1
                                      , vjust = 0)
-        , axis.title.x = element_text(size = 15)
-        , axis.title.y = element_text(size = 15)
-        , plot.title = element_text(size = 20, hjust = 0.5)
-        , strip.text.x = element_text(size = 15, colour = "black")
-        , legend.title = element_text(color = "black", size = 20)
-        , legend.text = element_text(size = 15)
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_text(size = my_ats)
+        , plot.title = element_text(size = my_pts , hjust = 0.5)
+        , strip.text.x = element_text(size = my_fls, colour = "black")
+        , legend.title = element_text(color = "black", size = my_als)
+        , legend.text = element_text(size = my_ats)
         , legend.direction = "vertical") +
   labs(title = "Ligand Affinity"
        , x = ""
@@ -152,20 +122,108 @@ p3 = ggplot(df_lf_lig, aes(x = mutation_info
                      #, label = "p.format")
                      , label = "p.signif")
 
-p3
+p2
+
+#====================================================================
+#===========
+# Plot 3: Foldx
+#===========
+my_stat_foldx = compare_means(param_value~mutation_info, group.by = "param_type"
+                              , data = df_lf_foldx,  paired = FALSE, p.adjust.method = "BH")
+
+y_value = "param_value"
+
+p3 = ggplot(df_lf_foldx, aes(x = mutation_info
+                             , y = eval(parse(text=y_value)) ))  + 
+  facet_wrap(~ param_type
+             , nrow = 1
+             , scales = "free_y") + 
+  geom_boxplot(fill = "white", outlier.colour = NA
+               #, position = position_dodge(width = 0.2)
+               , width = 0.5) +
+  geom_point(position = position_jitterdodge(dodge.width=0.01)
+             , alpha = 0.5
+             , show.legend = FALSE
+             , aes(colour = factor(foldx_outcome))) +
+  theme(axis.text.x = element_text(size = my_ats)
+        , axis.text.y = element_text(size = my_ats
+                                     , angle = 0
+                                     , hjust = 1
+                                     , vjust = 0)
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_text(size = my_ats)
+        , plot.title = element_text(size = my_pts , hjust = 0.5)
+        , strip.text.x = element_text(size = my_fls, colour = "black")
+        #, legend.title = element_text(color = "black", size = my_als)
+        , legend.text = element_text(size = my_ats)
+        , legend.direction = "vertical"
+        , legend.title = element_blank()) +
+  labs(title = ""
+       , x = ""
+       , y = "") + 
+  stat_compare_means(comparisons = my_comparisons
+                     , method = "wilcox.test"
+                     , paired = FALSE
+                     #, label = "p.format")
+                     , label = "p.signif")
+
+p3 
+
+#====================================================================
+#===========
+# legend
+#===========
+
+legend = ggplot(df_lf_foldx, aes(x = mutation_info
+                             , y = eval(parse(text=y_value)) ))  + 
+  facet_wrap(~ param_type
+             , nrow = 1
+             , scales = "free_y") + 
+  geom_boxplot(fill = "white", outlier.colour = NA
+               #, position = position_dodge(width = 0.2)
+               , width = 0.5) +
+  geom_point(position = position_jitterdodge(dodge.width=0.01)
+             , aes(colour = factor(foldx_outcome))) +
+  theme(legend.text = element_text(size = 25)
+        , legend.direction = "vertical"
+        , legend.title = element_blank())+
+
+  guides(color = guide_legend(override.aes = list(size = 6)))
+
+legend
 
 #===========================
 # combine
 #===========================
-#svg(plot_or_combined, width = 32, height = 12)
-svg("test.svg", width = 25, height = 12)
-#theme_set(theme_gray()) # to preserve default theme
+#---------
+# plot 1
+#---------
+cat("Output plot:",plot_dr_other_combined)
+svg(plot_dr_other_combined, width = 24, height = 12)
 
-printFile = cowplot::plot_grid(plot_grid(p1, p2, p3
-                                         , nrow = 3
-                                         , align = 'h'
-                                         , labels = c("", "", "")
-                                         , label_size = 20))
-print(printFile)
+#theme_set(theme_gray()) # to preserve default theme
+OutPlot = cowplot::plot_grid(p1, p2
+                             , nrow = 2
+                             , align = "hv"
+                             , axis = "b"
+                             , labels = c("", "", "")
+                             , label_size = my_als)
+print(OutPlot)
 dev.off()
 
+
+#---------
+# plot 2
+#---------
+svg(plot_dr_other_foldx , width = 6, height = 7)
+OutPlot2 =  p3
+print(OutPlot2)
+dev.off()
+
+#---------
+# plot 3: legend
+#---------
+svg(plot_point_legend, width = 6, height = 7)
+OutPlot3 =  legend
+print(OutPlot3)
+dev.off()
diff --git a/scripts/plotting/other_plots_data.R b/scripts/plotting/other_plots_data.R
index a60af1e..1a0d73e 100644
--- a/scripts/plotting/other_plots_data.R
+++ b/scripts/plotting/other_plots_data.R
@@ -33,7 +33,7 @@ my_max = max(df_ps[,n]); my_max
 df_ps$foldx_scaled = ifelse(df_ps[,n] < 0
                             , df_ps[,n]/abs(my_min)
                             , df_ps[,n]/my_max) #335, 15
-#sanity check
+# sanity check
 my_min = min(df_ps$foldx_scaled); my_min 
 my_max = max(df_ps$foldx_scaled); my_max 
 
@@ -50,7 +50,6 @@ if ( all(c1 == c2) ){
   exit()
 }
 
-
 # name tidying
 df_ps$mutation_info = as.factor(df_ps$mutation_info)
 df_ps$duet_outcome = as.factor(df_ps$duet_outcome)
@@ -60,6 +59,21 @@ df_ps$ligand_outcome  = as.factor(df_ps$ligand_outcome)
 # check
 table(df_ps$mutation_info)
 
+ # further checks to make sure dr and other muts are indeed unique
+dr_muts = df_ps[df_ps$mutation_info == dr_muts_col,]
+dr_muts_names = unique(dr_muts$mutation)
+
+other_muts = df_ps[df_ps$mutation_info == other_muts_col,]
+other_muts_names = unique(other_muts$mutation)
+
+if ( table(dr_muts_names%in%other_muts_names)[[1]] == length(dr_muts_names) &&
+  table(other_muts_names%in%dr_muts_names)[[1]] == length(other_muts_names) ){
+  cat("PASS: dr and other muts are indeed unique")
+}else{
+  cat("FAIL: dr adn others muts are NOT unique!")
+  quit()
+}
+
 #%%%%%%%%%%%%%%%%%%%
 # REASSIGNMENT: LIG
 #%%%%%%%%%%%%%%%%%%%%
@@ -133,78 +147,25 @@ levels(df_lf_ps$mutation_info)[levels(df_lf_ps$mutation_info)==other_muts_col] <
 levels(df_lf_ps$mutation_info); table(df_lf_ps$mutation_info)
 
 ############################################################################
-#===========
-# Data: foldx
-#===========
-# keep similar dtypes cols together
-cols_to_select_foldx = c("mutationinformation", "mutation", "position", "mutation_info"
-                      , "foldx_outcome"
-                      
-                      , "foldx_scaled"
-                      , "ligand_distance"
-                      , "asa"
-                      , "rsa"
-                      , "rd_values"
-                      , "kd_values")
 
-
-df_wf_foldx = df_ps[, cols_to_select_foldx]
-
-pivot_cols_foldx = cols_to_select_foldx[1:5]; pivot_cols_foldx
-  
-expected_rows_lf_foldx = nrow(df_wf_foldx) * (length(df_wf_foldx) - length(pivot_cols_foldx))
-expected_rows_lf_foldx
-
-# LF data: foldx
-df_lf_foldx = gather(df_wf_foldx, param_type, param_value, foldx_scaled:kd_values, factor_key=TRUE)
-
-if (nrow(df_lf_foldx) == expected_rows_lf_foldx){
-  cat("PASS: long format data created for foldx")
-}else{
-  cat("FAIL: long format data could not be created for foldx")
-  exit()
-}
-
-# assign pretty labels: param type
-levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
-
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="foldx_scaled"] <- "Foldx"
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="ligand_distance"] <- "Ligand Distance"
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="asa"] <- "ASA"
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rsa"] <- "RSA"
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rd_values"] <- "RD"
-levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="kd_values"] <- "KD"
-# check
-levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
-
-# assign pretty labels: mutation_info
-levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
-sum(table(df_lf_foldx$mutation_info)) == nrow(df_lf_foldx)
-
-levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==dr_muts_col] <- "DM"
-levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==other_muts_col] <- "OM"
-# check
-levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
-
-############################################################################
 #===========
 # LF data: LIG
 #===========
 # keep similar dtypes cols together
 cols_to_select_lig = c("mutationinformation", "mutation", "position", "mutation_info"
-                         , "ligand_outcome"
-
-                         , "affinity_scaled"
-                         , "ligand_distance"
-                         , "asa"
-                         , "rsa"
-                         , "rd_values"
-                         , "kd_values")
+                       , "ligand_outcome"
+                       
+                       , "affinity_scaled"
+                       , "ligand_distance"
+                       , "asa"
+                       , "rsa"
+                       , "rd_values"
+                       , "kd_values")
 
 df_wf_lig = df_lig[, cols_to_select_lig]
 
 pivot_cols_lig = cols_to_select_lig[1:5]; pivot_cols_lig
-  
+
 expected_rows_lf_lig = nrow(df_wf_lig) * (length(df_wf_lig) - length(pivot_cols_lig))
 expected_rows_lf_lig
 
@@ -239,7 +200,61 @@ levels(df_lf_lig$mutation_info)[levels(df_lf_lig$mutation_info)==other_muts_col]
 # check
 levels(df_lf_lig$mutation_info); table(df_lf_lig$mutation_info)
 
-###############################################################################
+#############################################################################
+#===========
+# Data: foldx
+#===========
+# keep similar dtypes cols together
+cols_to_select_foldx = c("mutationinformation", "mutation", "position", "mutation_info"
+                      , "foldx_outcome"
+                      
+                      , "foldx_scaled")
+                      #, "ligand_distance"
+                      #, "asa"
+                      #, "rsa"
+                      #, "rd_values"
+                      #, "kd_values")
+
+
+df_wf_foldx = df_ps[, cols_to_select_foldx]
+
+pivot_cols_foldx = cols_to_select_foldx[1:5]; pivot_cols_foldx
+  
+expected_rows_lf_foldx = nrow(df_wf_foldx) * (length(df_wf_foldx) - length(pivot_cols_foldx))
+expected_rows_lf_foldx
+
+# LF data: foldx
+df_lf_foldx = gather(df_wf_foldx, param_type, param_value, foldx_scaled, factor_key=TRUE)
+
+if (nrow(df_lf_foldx) == expected_rows_lf_foldx){
+  cat("PASS: long format data created for foldx")
+}else{
+  cat("FAIL: long format data could not be created for foldx")
+  exit()
+}
+
+# assign pretty labels: param type
+levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
+
+levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="foldx_scaled"] <- "Foldx"
+#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="ligand_distance"] <- "Ligand Distance"
+#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="asa"] <- "ASA"
+#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rsa"] <- "RSA"
+#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rd_values"] <- "RD"
+#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="kd_values"] <- "KD"
+# check
+levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
+
+# assign pretty labels: mutation_info
+levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
+sum(table(df_lf_foldx$mutation_info)) == nrow(df_lf_foldx)
+
+levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==dr_muts_col] <- "DM"
+levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==other_muts_col] <- "OM"
+# check
+levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
+
+############################################################################
 
 # clear excess variables
 rm(cols_to_select_ps, cols_to_select_foldx, cols_to_select_lig
diff --git a/scripts/plotting/test.R b/scripts/plotting/test.R
deleted file mode 100644
index 8033517..0000000
--- a/scripts/plotting/test.R
+++ /dev/null
@@ -1,96 +0,0 @@
-setwd("/home/tanu/git/LSHTM_analysis/scripts/plotting")
-
-source("combining_dfs_plotting.R")
-
-table(merged_df3$mutation_info)
-
-# assign foldx
-#ddg<0 = "Stabilising" (-ve)
-table(merged_df3$ddg < 0)
-merged_df3$foldx_outcome = ifelse(merged_df3$ddg < 0, "Stabilising", "Destabilising")
-
-#===========
-# PS data
-#===========
-dr_muts = merged_df3[merged_df3$mutation_info == "dr_mutations_pyrazinamide",]
-other_muts = merged_df3[merged_df3$mutation_info == "other_mutations_pyrazinamide",]
-
-par(mfrow = c(1,1))
-par(mfrow = c(2,6))
-
-# mcsm duet
-boxplot(dr_muts$duet_scaled, other_muts$duet_scaled, main = "DUET"
-        #, col = factor(merged_df3$duet_outcome)
-        )
-wilcox.test(dr_muts$duet_scaled, other_muts$duet_scaled, paired = F)
-
-# foldx ddg
-boxplot(dr_muts$ddg, other_muts$ddg, main = "Foldx")
-wilcox.test(dr_muts$ddg, other_muts$ddg, paired = F)
-
-# rd
-boxplot(dr_muts$rd_values, other_muts$rd_values, main = "RD")
-wilcox.test(dr_muts$rd_values, other_muts$rd_values)
-
-# kd
-boxplot(dr_muts$kd_values, other_muts$kd_values, main = "KD")
-wilcox.test(dr_muts$kd_values, other_muts$kd_values)
-
-# asa
-boxplot(dr_muts$asa, other_muts$asa, main = "ASA")
-wilcox.test(dr_muts$asa, other_muts$asa)
-
-# rsa
-boxplot(dr_muts$rsa, other_muts$rsa, main = "RSA")
-wilcox.test(dr_muts$rsa, other_muts$rsa)
-
-#===================================================================
-#==========
-# LIG data
-#==========
-dr_muts_lig = merged_df3_lig[merged_df3_lig$mutation_info == "dr_mutations_pyrazinamide",]
-other_muts_lig = merged_df3_lig[merged_df3_lig$mutation_info == "other_mutations_pyrazinamide",]
-
-# mcsm ligand affinity
-boxplot(dr_muts_lig$duet_scaled, other_muts_lig$duet_scaled, main = "Ligand affinity")
-wilcox.test(dr_muts_lig$duet_scaled, other_muts_lig$duet_scaled, paired = F)
-
-# rd
-boxplot(dr_muts_lig$rd_values, other_muts_lig$rd_values, main = "RD")
-wilcox.test(dr_muts_lig$rd_values, other_muts_lig$rd_values)
-
-# kd
-boxplot(dr_muts_lig$kd_values, other_muts_lig$kd_values, main = "KD")
-wilcox.test(dr_muts_lig$kd_values, other_muts_lig$kd_values)
-
-# asa
-boxplot(dr_muts_lig$asa, other_muts_lig$asa, main = "ASA")
-wilcox.test(dr_muts_lig$asa, other_muts_lig$asa)
-
-# rsa
-boxplot(dr_muts_lig$rsa, other_muts_lig$rsa, main = "RSA")
-wilcox.test(dr_muts_lig$rsa, other_muts_lig$rsa)
-
-# checking agreement b/w mcsm and foldx
-cols_to_select = c("mutationinformation"
-                   , "mutation_info"
-                   , "duet_scaled"
-                   , "ddg"
-                   , "duet_outcome"
-                   , "foldx_outcome")
-
-merged_df3_short = select(merged_df3, cols_to_select)
-
-mcsm_foldx = merged_df3_short[which(merged_df3_short$duet_outcome != merged_df3_short$foldx_outcome),]
-
-mcsm_foldx$sign_comp = ifelse(sign(mcsm_foldx$duet_scaled)==sign(mcsm_foldx$ddg), "PASS", "FAIL")
-table(mcsm_foldx$sign_comp)
-
-# another way of checking
-merged_df3$sign_comp = ifelse(sign(merged_df3$duet_scaled)==sign(merged_df3$ddg), "PASS", "FAIL")
-table(merged_df3$sign_comp)
-
-disagreement = table(merged_df3$sign_comp)[2]/nrow(merged_df3)*100
-agreement = 100 - disagreement
-
-cat("There is", agreement, "% between mcsm and foldx predictions")