import commit

mcsm_analysis/pyrazinamide/scripts/plotting/basic_barplots_LIG.R

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+getwd()
+setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting")
+getwd()
+
+########################################################################
+# 				Installing and loading required packages 			   #
+########################################################################
+
+source("../Header_TT.R")
+
+#require(data.table)
+#require(dplyr)
+
+########################################################################
+#		 Read file: call script for combining df for lig		   	   #
+########################################################################
+
+source("../combining_two_df_lig.R") 
+
+#---------------------- PAY ATTENTION
+# the above changes the working dir
+#[1] "git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts"
+#---------------------- PAY ATTENTION
+
+#==========================
+# This will return:
+
+# df with NA:
+# merged_df2
+# merged_df3
+
+# df without NA:
+# merged_df2_comp
+# merged_df3_comp
+#===========================
+
+###########################
+# Data for Lig plots
+# you need merged_df3
+# or
+# merged_df3_comp
+# since these have unique SNPs
+# I prefer to use the merged_df3
+# because using the _comp dataset means
+# we lose some muts and at this level, we should use
+# as much info as available
+###########################
+
+# uncomment as necessary
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+# REASSIGNMENT
+my_df  = merged_df3
+#my_df = merged_df3_comp
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+
+# delete variables not required
+rm(merged_df2, merged_df2_comp, merged_df3, merged_df3_comp)
+
+# quick checks
+colnames(my_df)
+str(my_df)
+
+# Ensure correct data type in columns to plot: need to be factor
+# sanity check
+is.factor(my_df$Lig_outcome)
+my_df$Lig_outcome = as.factor(my_df$lig_outcome)
+is.factor(my_df$Lig_outcome)
+#[1] TRUE
+
+#############################
+# Extra sanity check:
+# for mcsm_lig ONLY
+# Dis_lig_Ang should be <10
+#############################
+
+if (max(my_df$Dis_lig_Ang) < 10){
+  print ("Sanity check passed: lig data is <10Ang")
+}else{
+  print ("Error: data should be filtered to be within 10Ang")
+}
+
+########################################################################
+#               end of data extraction and cleaning for plots          #
+########################################################################
+
+#===========================
+# Plot: Basic barplots 
+#===========================
+
+#===================
+# Data for plots
+#===================
+
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+# REASSIGNMENT 
+df  = my_df 
+#<<<<<<<<<<<<<<<<<<<<<<<<<
+rm(my_df)
+
+# sanity checks
+str(df)
+
+if (identical(df$Position, df$position)){
+  print("Sanity check passed: Columns 'Position' and 'position' are identical")
+} else{
+  print("Error!: Check column names and info contained")
+}
+
+#****************
+# generate plot: No of stabilising and destabilsing muts
+#****************
+# set output dir for plots
+getwd()
+setwd("~/git/Data/pyrazinamide/output/plots")
+getwd()
+
+svg('basic_barplots_LIG.svg')
+
+my_ats = 25 # axis text size
+my_als = 22 # axis label size
+
+# uncomment as necessary for either directly outputting results or 
+# printing on the screen
+g = ggplot(df, aes(x = Lig_outcome))
+#prinfFile = g + geom_bar(
+  g + geom_bar(
+  aes(fill = Lig_outcome)
+  , show.legend = TRUE
+) + geom_label(
+  stat = "count"
+  , aes(label = ..count..)
+  , color = "black"
+  , show.legend = FALSE
+  , size = 10) + theme(
+    axis.text.x = element_blank()
+    , axis.title.x = element_blank()
+    , axis.title.y = element_text(size=my_als)
+    , axis.text.y = element_text(size = my_ats)
+    , legend.position = c(0.73,0.8)
+    , legend.text = element_text(size=my_als-2)
+    , legend.title = element_text(size=my_als)
+    , plot.title = element_blank()
+  ) + labs(
+    title = ""
+    , y = "Number of SNPs"
+    #, fill='Ligand Outcome'
+  )  + scale_fill_discrete(name = "Ligand Outcome"
+                           , labels = c("Destabilising", "Stabilising"))
+print(prinfFile)
+dev.off()
+
+#****************
+# generate plot: No of positions
+#****************
+#get freq count of positions so you can subset freq<1
+#require(data.table)
+setDT(df)[, pos_count := .N, by = .(Position)] #169, 36
+
+head(df$pos_count)
+table(df$pos_count)
+# this is cummulative
+#1  2  3  4  5  6 
+#5 24 36 56 30 18 
+
+# use group by on this
+snpsBYpos_df <- df %>%
+  group_by(Position) %>%
+  summarize(snpsBYpos = mean(pos_count)) 
+
+table(snpsBYpos_df$snpsBYpos)
+#1  2  3  4  5  6 
+#5 12 12 14  6  3
+# this is what will get plotted
+
+svg('position_count_LIG.svg')
+
+my_ats = 25 # axis text size
+my_als = 22 # axis label size
+
+g = ggplot(snpsBYpos_df, aes(x = snpsBYpos))
+prinfFile = g + geom_bar(
+  #g + geom_bar(
+  aes (alpha = 0.5)
+  , show.legend = FALSE
+) +
+  geom_label(
+    stat = "count", aes(label = ..count..)
+    , color = "black"
+    , size = 10
+  ) +
+  theme( 
+    axis.text.x = element_text(
+      size = my_ats
+      , angle = 0
+    )
+    , axis.text.y = element_text(
+      size = my_ats
+      , angle = 0
+      , hjust = 1
+    )
+    , axis.title.x = element_text(size = my_als)
+    , axis.title.y = element_text(size = my_als)
+    , plot.title = element_blank()
+  ) +
+  labs(
+    x = "Number of SNPs"
+    , y = "Number of Sites"
+  )
+print(prinfFile)
+dev.off()
+########################################################################
+#               			end of Lig barplots         			   #
+########################################################################
+
+