calculating mean stabilty per position

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scripts/af_or_calcs.R

@@ -17,7 +17,7 @@ spec = matrix(c(
   "gene"   , "g", 1, "character"
 ), byrow = TRUE, ncol = 4)
 
-opt = getopt(spec);
+opt = getopt(spec)
 
 drug = opt$drug
 gene = opt$gene

scripts/plotting/barplots_subcolours_PS.R

@@ -81,9 +81,9 @@ if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformati
   my_df_u = my_df
 }
 
-#upos = unique(my_df_u$position)
+upos = unique(my_df_u$position)
 cat('Dim of clean df:'); cat(dim(my_df_u))
-cat('\nNo. of unique mutational positions:'); cat(length(unique(my_df_u$position)))
+cat('\nNo. of unique mutational positions:'); cat(length(upos))
 
 ########################################################################
 #               end of data extraction and cleaning for plots          #

scripts/plotting/basic_barplots_PS.R

@@ -17,9 +17,9 @@ getwd()
 ########################################################################
 #		 Read file: call script for combining df for PS			   	   #
 ########################################################################
-
+#source("../combining_two_df.R")
 #?????????????
-#
+
 #########################################################
 #%% variable assignment: input and output paths & filenames
 drug = 'pyrazinamide'
@@ -87,9 +87,9 @@ if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformati
   my_df_u = my_df
 }
 
-#upos = unique(my_df_u$position)
+upos = unique(my_df_u$position)
 cat('Dim of clean df:'); cat(dim(my_df_u))
-cat('\nNo. of unique mutational positions:'); cat(length(unique(my_df_u$position)))
+cat('\nNo. of unique mutational positions:'); cat(length(upos))
   
 ########################################################################
 #               end of data extraction and cleaning for plots          #

scripts/plotting/mcsm_mean_stability.R

@@ -0,0 +1,163 @@
+getwd()
+setwd('~/git/LSHTM_analysis/scripts/plotting')
+getwd()
+
+#########################################################
+# TASK:
+
+#########################################################
+source("Header_TT.R")
+require(data.table)
+require(dplyr)
+#========================================================
+#	Read file: call script for combining df for PS
+#source("../combining_two_df.R")
+
+#???????????
+
+#========================================================
+#%% variable assignment: input and output paths & filenames
+drug = 'pyrazinamide'
+gene = 'pncA'
+gene_match = paste0(gene,'_p.')
+cat(gene_match)
+
+#=============
+# directories
+#=============
+datadir = paste0('~/git/Data')
+indir = paste0(datadir, '/', drug, '/input')
+outdir = paste0('~/git/Data', '/', drug, '/output')
+
+#======
+# input
+#======
+#in_filename = 'mcsm_complex1_normalised.csv'
+in_filename_params = paste0(tolower(gene), '_all_params.csv') 
+infile_params = paste0(outdir, '/', in_filename_params)
+cat(paste0('Input file 1:', infile_params) )
+
+#=======
+# output
+#=======
+out_filename_mean_stability = paste0(tolower(gene), "_mean_stability.csv") 
+outfile_mean_stability = paste0(outdir, "/", out_filename_mean_stability)
+print(paste0("Output file:", outfile_mean_stability))
+
+#%%===============================================================
+###########################
+# Read file: struct params
+###########################
+cat('Reading struct params including mcsm:', in_filename_params)
+
+my_df = read.csv(infile_params
+                 #, stringsAsFactors = F
+                 , header = T)
+
+cat('Input dimensions:', dim(my_df)) 
+
+# clear variables
+rm(in_filename_params, infile_params)
+
+# quick checks
+colnames(my_df)
+str(my_df)
+
+# check for duplicate mutations
+if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformation)){
+  cat(paste0('CAUTION:', ' Duplicate mutations identified'
+             , '\nExtracting these...'))
+  dup_muts = my_df[duplicated(my_df$mutationinformation),]
+  dup_muts_nu = length(unique(dup_muts$mutationinformation))
+  cat(paste0('\nDim of duplicate mutation df:', nrow(dup_muts)
+             , '\nNo. of unique duplicate mutations:', dup_muts_nu
+             , '\n\nExtracting df with unique mutations only'))
+  my_df_u = my_df[!duplicated(my_df$mutationinformation),]
+}else{
+  cat(paste0('No duplicate mutations detected'))
+  my_df_u = my_df
+}
+
+upos = unique(my_df_u$position)
+cat('Dim of clean df:')
+cat(dim(my_df_u))
+cat('\nNo. of unique mutational positions:'); cat(length(upos))
+
+########################################################################
+#               end of data extraction and cleaning for plots          #
+########################################################################
+#================
+# Data for plots
+#================
+# REASSIGNMENT as necessary
+df  = my_df_u
+rm(my_df)
+
+###########################
+# Data for bfactor figure
+# PS average 
+# Lig average
+###########################
+head(df$position); head(df$mutationinformation)
+head(df$duet_scaled)
+
+# order data frame 
+#df = df[order(df$position),] #already done
+
+head(df$position); head(df$mutationinformation)
+head(df$duet_scaled)
+
+#***********
+# PS: average by position
+#***********
+mean_duet_by_position <- df %>%
+  group_by(position) %>%
+  summarize(averaged.duet = mean(duet_scaled))
+
+#***********
+# Lig: average by position
+#***********
+mean_affinity_by_position <- df %>%
+  group_by(position) %>%
+  summarize(averaged.affinity = mean(affinity_scaled))
+
+#***********
+# cbind:mean_duet_by_position and mean_affinity_by_position
+#***********
+
+combined = as.data.frame(cbind(mean_duet_by_position, mean_affinity_by_position ))
+
+# sanity check
+# mean_PS_affinity_Bfactor
+
+colnames(combined)
+
+colnames(combined) = c("position"
+                       , "average_duet_scaled"
+                       , "position2"
+                       , "average_affinity_scaled")
+
+colnames(combined)
+
+identical(combined$position, combined$position2)
+
+n = which(colnames(combined) == "position2"); n
+
+combined_df = combined[,-n]
+
+max(combined_df$average_duet_scaled) ; min(combined_df$average_duet_scaled)
+
+max(combined_df$average_affinity_scaled) ; min(combined_df$average_affinity_scaled)
+
+head(combined_df$position); tail(combined_df$position)
+#%%============================================================
+# output
+write.csv(combined_df, outfile_mean_stability
+          , row.names = F)
+cat("Finished writing file:\n"
+    , outfile_mean_stability
+    , "\nNo. of rows:", nrow(combined_df)
+    , "\nNo. of cols:", ncol(combined_df))
+
+# end of script
+#===============================================================

scripts/plotting/subcols_axis_PS.R

@@ -80,9 +80,9 @@ if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformati
   my_df_u = my_df
 }
 
-#upos = unique(my_df_u$position)
+upos = unique(my_df_u$position)
 cat('Dim of clean df:'); cat(dim(my_df_u))
-cat('\nNo. of unique mutational positions:'); cat(length(unique(my_df_u$position)))
+cat('\nNo. of unique mutational positions:'); cat(length(upos))
 #======================================================
 # create a new df with unique position numbers and cols
 position = unique(my_df$position) #130