renamed files for lineage_diff_sensitivites.R

scripts/plotting/plotting_thesis/embb/embb_lineage_diff_sensitivities.R

@@ -45,20 +45,10 @@ lef_snps_df = df2[df2$mutationinformation%in%left_snps,]
 table(lef_snps_df$lineage)
 
 ##################################
-# selected lineage plos
+# selected lineage plots
-cols_to_subset = c("mutationinformation"
+##################################
-                  , "lineage"
-                  , "dst2"
-                  , "sens2")
-
-
 #-----------------------------------------------
-# step 0: Subset a smaller df
+# step 0: Select muts for each target
-#-----------------------------------------------
-plot_df_gene = df2_lin[, cols_to_subset]
-
-#-----------------------------------------------
-# step 1: Select muts for each target
 #-----------------------------------------------
 # embb
 #sel_mutsP = c("D354N", "Y319D", "Y319D", "A962P", "S651N", "A201S")
@@ -69,6 +59,18 @@ sel_mutsP = c("P75R", "A19G", "A133P", "R154W", "R118L") #G30D)
 # rpob
 #sel_mutsP = c("")
 #-----------------------------------------------
+# step 1: Subset a smaller df
+#-----------------------------------------------
+# selected lineage plos
+cols_to_subset = c("mutationinformation"
+                  , "lineage"
+                  , "dst2"
+                  , "sens2")
+
+
+
+plot_df_gene = df2_lin[, cols_to_subset]
+#-----------------------------------------------
 # step 2: Subset data with just those genes
 #-----------------------------------------------
 plot_df_gene = plot_df_gene[plot_df_gene$mutationinformation%in%sel_mutsP,]
@@ -82,9 +84,9 @@ plot_df = plot_df_gene
 
 #-----------------------------------------------
 # step 4: Add p-value
+# NOT NEEDED, get it from lineage_diff_sensitivities.R if needed
 #-----------------------------------------------
 
-
 #-----------------------------------------------
 # step 5: Plot 
 #-----------------------------------------------

scripts/plotting/plotting_thesis/gid/gid_lineage_diff_sensitivities.R

@@ -0,0 +1,136 @@
+#=============
+# Data: Input
+#==============
+#source("~/git/LSHTM_analysis/config/embb.R")
+source("~/git/LSHTM_analysis/config/gid.R")
+
+source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
+
+
+# Now we need to make a column that fill na  in dst with value of dst_mode
+df2 = merged_df2
+#table(df2$dst2)
+
+df2$dst2 = ifelse(is.na(df2$dst), df2$dst_mode, df2$dst)
+df2$sens2 = ifelse(df2$dst2 == 1, "R", "S")
+table(df2$sens2)
+
+
+all_snps    = unique(df2$mutationinformation)
+all_snps_n  = length(all_snps); all_snps_n
+
+all_samples_id = unique(df2$id)  # different to nrows
+all_samples_id_n = length(all_samples_id); all_samples_id_n # different to nrows
+
+sel_lineage   = c("L1", "L2", "L3", "L4")
+df2_lin = df2[df2$lineage%in%sel_lineage,]
+sel_lin_snps    = unique(df2_lin$mutationinformation)
+sel_lin_snps_n   = length(sel_lin_snps); sel_lin_snps_n
+
+sel_lin_samples_id = unique(df2_lin$id)
+sel_lin_samples_id_n = length(sel_lin_samples_id);sel_lin_samples_id_n
+
+# are the snps that are not in L1-L4 unique to L5-L7
+left_snps = all_snps[!all_snps%in%sel_lin_snps]
+left_snps_n = length(left_snps); left_snps_n
+
+if (all_snps_n == sel_lin_snps_n+left_snps_n){
+  cat("PASS: left snps extracted for gene", tolower(gene))
+}else{
+  stop("Abort: left snps count mismatch")
+}
+
+left_snps
+lef_snps_df = df2[df2$mutationinformation%in%left_snps,]
+table(lef_snps_df$lineage)
+
+##################################
+# selected lineage plots
+##################################
+#-----------------------------------------------
+# step 0: Select muts for each target
+#-----------------------------------------------
+# embb
+#sel_mutsP = c("D354N", "Y319D", "Y319D", "A962P", "S651N", "A201S")
+# gid
+sel_mutsP = c("P75R", "A19G", "A133P", "R154W", "R118L") #G30D)
+# katg
+#sel_mutsP = c("")
+# rpob
+#sel_mutsP = c("")
+#-----------------------------------------------
+# step 1: Subset a smaller df
+#-----------------------------------------------
+cols_to_subset = c("mutationinformation"
+                  , "lineage"
+                  , "dst2"
+                  , "sens2")
+
+
+
+plot_df_gene = df2_lin[, cols_to_subset]
+#-----------------------------------------------
+# step 2: Subset data with just those genes
+#-----------------------------------------------
+plot_df_gene = plot_df_gene[plot_df_gene$mutationinformation%in%sel_mutsP,]
+cat("\nnrow of plot_df:", nrow(plot_df_gene))
+table(plot_df_gene$sens2, plot_df_gene$lineage, plot_df_gene$mutationinformation)
+#-----------------------------------------------
+# step 3: Assign to plot_df
+#-----------------------------------------------
+
+plot_df = plot_df_gene
+
+#-----------------------------------------------
+# step 4: Add p-value
+# NOT NEEDED, get it from lineage_diff_sensitivities.R if needed
+#-----------------------------------------------
+
+
+#-----------------------------------------------
+# step 5: Plot 
+#-----------------------------------------------
+p_title = gene
+ts = 8
+gls = 3
+DSplot = ggplot(plot_df, aes(x = lineage,
+                    fill = sens2)) + 
+  geom_bar(stat = 'count') +
+  scale_fill_manual(name = ""
+                    # name = leg_title
+                    , values = c("red", "blue")
+                    #, labels = levels(sens2))
+  )+
+  facet_wrap(~mutationinformation
+             , scales = 'free_y'
+             #, ncol = 3
+             , nrow = 1
+  ) +
+  theme(legend.position = "top"
+        , plot.title = element_text(hjust = 0.5, size=15,face = "italic")
+        #, plot.title = element_blank()
+        
+        , strip.text = element_text(size=ts+2)
+        , axis.text.x = element_text(size=ts)
+        , axis.text.y = element_text(size=ts)
+        , axis.title.y = element_text(size=ts)
+        , legend.title = element_blank()
+        , axis.title.x = element_blank()
+  )+
+  labs(title = paste0(p_title
+                      #, ": sensitivity by lineage"
+                      ),
+       y = 'Sample Count') #+
+  #geom_text(aes(label = pvalRF, x = 2.5, y =  ypos_label+0.75))
+ # geom_blank(aes(y = ypos_label+1.25)) +
+#  geom_label(aes(label = pvalRF, x = 2.5, ypos_label+0.75), fill="white", size =gls)
+
+#========
+# Outplot
+#========
+outdir_lin = "/home/pub/Work/LSHTM/Thesis_Plots/"
+png(paste0(outdir_lin, tolower(gene), "_linDS_selected.png")
+    , width = 8
+    , height = 3, units = "in", res = 300 ) 
+DSplot
+dev.off()

scripts/plotting/plotting_thesis/katg/katg_lineage_diff_sensitivities.R

@@ -42,6 +42,8 @@ left_snps
 lef_snps_df = df2[df2$mutationinformation%in%left_snps,]
 table(lef_snps_df$lineage)
 
+##################################
+# selected lineage plots
 ##################################
 #-----------------------------------------------
 # step 0: Select muts for each target
@@ -81,9 +83,9 @@ plot_df = plot_df_gene
 
 #-----------------------------------------------
 # step 4: Add p-value
+# NOT NEEDED, get it from lineage_diff_sensitivities.R if needed
 #-----------------------------------------------
 
-
 #-----------------------------------------------
 # step 5: Plot 
 #-----------------------------------------------

scripts/plotting/plotting_thesis/lineage_diff_sensitivities.R

@@ -1,15 +1,12 @@
 #=============
 # Data: Input
 #==============
-#source("~/git/LSHTM_analysis/config/embb.R")
+source("~/git/LSHTM_analysis/config/embb.R")
-source("~/git/LSHTM_analysis/config/gid.R")
-
 source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
 
 
 # Now we need to make a column that fill na  in dst with value of dst_mode
 df2 = merged_df2
-#table(df2$dst2)
 
 df2$dst2 = ifelse(is.na(df2$dst), df2$dst_mode, df2$dst)
 df2$sens2 = ifelse(df2$dst2 == 1, "R", "S")
@@ -45,39 +42,40 @@ lef_snps_df = df2[df2$mutationinformation%in%left_snps,]
 table(lef_snps_df$lineage)
 
 ##################################
+# selected lineage plots
+##################################
+#-----------------------------------------------
+# step 0: Select muts for each target
+#-----------------------------------------------
+# embb
+#sel_mutsP = c("D354N", "Y319D", "Y319D", "A962P", "S651N", "A201S")
+# gid
+#sel_mutsP = c("")
+# katg
+#sel_mutsP = c("")
+# rpob
+#sel_mutsP = c("")
 # selected lineage plos
+
+#-----------------------------------------------
+# step 1: Subset a smaller df
+#-----------------------------------------------
 cols_to_subset = c("mutationinformation"
                   , "lineage"
                   , "dst2"
                   , "sens2")
 
-
-#-----------------------------------------------
-# step 0: Subset a smaller df
-#-----------------------------------------------
 plot_df_gene = df2_lin[, cols_to_subset]
 
-#-----------------------------------------------
-# step 1: Select muts for each target
-#-----------------------------------------------
-# embb
-#sel_mutsP = c("D354N", "Y319D", "Y319D", "A962P", "S651N", "A201S")
-# gid
-sel_mutsP = c("P75R", "A19G", "A133P", "R154W", "R118L") #G30D)
-# katg
-#sel_mutsP = c("")
-# rpob
-#sel_mutsP = c("")
 #-----------------------------------------------
 # step 2: Subset data with just those genes
 #-----------------------------------------------
 plot_df_gene = plot_df_gene[plot_df_gene$mutationinformation%in%sel_mutsP,]
 cat("\nnrow of plot_df:", nrow(plot_df_gene))
-table(plot_df_gene$sens2, plot_df_gene$lineage, plot_df_gene$mutationinformation)
+
 #-----------------------------------------------
 # step 3: Assign to plot_df
 #-----------------------------------------------
-
 plot_df = plot_df_gene
 
 #-----------------------------------------------
@@ -160,7 +158,7 @@ DSplot = ggplot(plot_df, aes(x = lineage,
 #========
 outdir_lin = "/home/pub/Work/LSHTM/Thesis_Plots/"
 png(paste0(outdir_lin, tolower(gene), "_linDS_selected.png")
-    , width = 8
+    , width = 4
-    , height = 3, units = "in", res = 300 ) 
+    , height = 4, units = "in", res = 300 ) 
 DSplot
 dev.off()

scripts/plotting/plotting_thesis/rpob/rpob_lineage_diff_sensitivities.R

@@ -41,6 +41,8 @@ left_snps
 lef_snps_df = df2[df2$mutationinformation%in%left_snps,]
 table(lef_snps_df$lineage)
 
+##################################
+# selected lineage plots
 ##################################
 #-----------------------------------------------
 # step 0: Select muts for each target
@@ -81,9 +83,9 @@ plot_df = plot_df_gene
 
 #-----------------------------------------------
 # step 4: Add p-value
+# NOT NEEDED, get it from lineage_diff_sensitivities.R if needed
 #-----------------------------------------------
 
-
 #-----------------------------------------------
 # step 5: Plot 
 #-----------------------------------------------