changes made to combining_dfs_plotting.R

scripts/functions/combining_dfs_plotting.R

@@ -2,11 +2,12 @@
 
 ###########################################################
 # TASK: To combine mcsm combined file and meta data.
-# This script is sourced from other .R scripts for plotting.
+# This script is sourced by other .R scripts for plotting.
 ###########################################################
-
 # load libraries and functions
 
+#source("Header_TT.R")
+
 #==========================================================
 # combining_dfs_plotting(): 
 
@@ -34,27 +35,6 @@ combining_dfs_plotting <- function(  my_df_u
                                    , gene_metadata
                                    , lig_dist_colname = 'ligand_distance'
                                    , lig_dist_cutoff = 10){
-  # #======================================
-  # # 1: Read file: <gene>_meta data.csv
-  # #======================================
-  # cat("\nReading meta data file:", df1_mcsm_comb)
-  # 
-  # my_df_u <- read.csv(df1_mcsm_comb
-  #                     , stringsAsFactors = F
-  #                     , header = T)
-  # cat("\nDim:", dim(my_df_u))
-  # 
-  # #======================================
-  # # 2: Read file: <gene>_meta data.csv
-  # #======================================
-  # cat("\nReading meta data file:", df2_gene_metadata)
-  # 
-  # gene_metadata <- read.csv(df2_gene_metadata
-  #                           , stringsAsFactors = F
-  #                           , header = T)
-  # cat("\nDim:", dim(gene_metadata))
-  # 
-  # table(gene_metadata$mutation_info)
 
   # counting NAs in AF, OR cols
   # or_mychisq
@@ -219,7 +199,6 @@ combining_dfs_plotting <- function(  my_df_u
         , "\nNA in AF:", sum(is.na(merged_df3$af_kin)))
   }
   
-  
   #===================================================
   # Merge3: merged_df2_comp
   # same as merge 1 but excluding NAs from ORs, etc.
@@ -273,6 +252,13 @@ combining_dfs_plotting <- function(  my_df_u
   # compare dfs: foo and merged_df3_com
   all.equal(foo, bar)
   #summary(comparedf(foo, bar))
+  cat("\n------------------------"
+      , "\nSummary of created dfs:"
+      , "\n------------------------"
+      , "\n1) Dim of merged_df2: " , nrow(merged_df2), "," , ncol(merged_df2)
+      , "\n2) Dim of merged_df2_comp: " , nrow(merged_df2_comp), "," , ncol(merged_df2_comp)
+      , "\n3) Dim of merged_df3: " , nrow(merged_df3), "," , ncol(merged_df3)
+      , "\n4) Dim of merged_df3_comp: " , nrow(merged_df3_comp), "," , ncol(merged_df3_comp))
   
   #####################################################################
   #                       Combining: LIG
@@ -281,13 +267,35 @@ combining_dfs_plotting <- function(  my_df_u
   #============
   # Merges 5-8
   #============
+  cat("\n=========================================="
+      , "\nStarting filtering for mcsm ligand df"
+      , "\n===========================================")
+  
+  if (lig_dist_colname%in%names(my_df_u)){
+    cat("\nFiltering column: ", lig_dist_colname
+        , "\nCut off criteria: ", lig_dist_cutoff, "Angstroms")
     df_lig = my_df_u[my_df_u[[lig_dist_colname]] < lig_dist_cutoff,]
   
-  merged_df2_lig = merged_df2[merged_df2$ligand_distance<lig_dist_cutoff,]
+    #merged_df2_lig = merged_df2[merged_df2$ligand_distance<lig_dist_cutoff,]
-  merged_df2_comp_lig = merged_df2_comp[merged_df2_comp$ligand_distance<lig_dist_cutoff,]
+    merged_df2_lig = merged_df2[merged_df2[[lig_dist_colname]] < lig_dist_cutoff,]
+    dim(merged_df2_lig)
     
-  merged_df3_lig = merged_df3[merged_df3$ligand_distance<lig_dist_cutoff,]
+    merged_df2_comp_lig = merged_df2_comp[merged_df2_comp[[lig_dist_colname]] < lig_dist_cutoff,]
-  merged_df3_comp_lig = merged_df3_comp[merged_df3_comp$ligand_distance<lig_dist_cutoff,]
+    
+    merged_df3_lig = merged_df3[merged_df3[[lig_dist_colname]] < lig_dist_cutoff,]
+    merged_df3_comp_lig = merged_df3_comp[merged_df3_comp[[lig_dist_colname]] < lig_dist_cutoff,]
+    
+    cat("\n------------------------"
+        , "\nSummary of created ligand dfs:"
+        , "\n------------------------"
+        , "\n1) Dim of merged_df2_lig: " , nrow(merged_df2_lig), "," , ncol(merged_df2_lig)
+        , "\n2) Dim of merged_df2_comp_lig: " , nrow(merged_df2_comp_lig), "," , ncol(merged_df2_comp_lig)
+        , "\n3) Dim of merged_df3_lig: " , nrow(merged_df3_lig), "," , ncol(merged_df3_lig)
+        , "\n4) Dim of merged_df3_comp_lig: " , nrow(merged_df3_comp_lig), "," , ncol(merged_df3_comp_lig))
+} else {
+    cat("\nFiltering column: ", lig_dist_colname, " not found\n")
+  }
+  #quit()
   
   # sanity check
   if (nrow(merged_df3_lig) == nrow(df_lig)){
@@ -327,8 +335,13 @@ combining_dfs_plotting <- function(  my_df_u
   #    , "\nNo. of cols: ", ncol(get(i)), "\n")
   #}
   
-  return(list(merged_df2, merged_df3
+  return(list(  merged_df2
-              , merged_df2_comp, merged_df3_comp
+              , merged_df3
-              , merged_df2_lig, merged_df3_lig))
+              , merged_df2_comp
+              , merged_df3_comp
+              , merged_df2_lig
+              , merged_df3_lig
+              , merged_df2_comp_lig
+              , merged_df3_comp_lig))
   
 }

scripts/functions/plotting_data.R

@@ -16,20 +16,18 @@ library(dplyr)
   ## my_df_u_lig
   ## dup_muts
 #========================================================
-plotting_data <- function(infile_params, mcsm_lig_cutoff = 10) {
+plotting_data <- function(df, lig_dist_colname = 'ligand_distance', lig_dist_cutoff = 10) {
 my_df       = data.frame()
 my_df_u     = data.frame()
 my_df_u_lig = data.frame()
 dup_muts    = data.frame()
   
-cat(paste0("\nInput file to prepare for plotting:", infile_params, "\n") )
-
 #===========================
 # Read file: struct params
 #===========================
-my_df = read.csv(infile_params, header = T)
+#df = read.csv(infile_params, header = T)
 
-cat("\nInput dimensions:", dim(my_df)) 
+cat("\nInput dimensions:", dim(df)) 
 
 #==================================
 # add foldx outcome category
@@ -43,17 +41,17 @@ cat("\nInput dimensions:", dim(my_df))
 # adding foldx scaled values
 # scale data b/w -1 and 1
 #------------------------------
-n = which(colnames(my_df) == "ddg"); n 
+n = which(colnames(df) == "ddg"); n 
 
-my_min = min(my_df[,n]); my_min 
+my_min = min(df[,n]); my_min 
-my_max = max(my_df[,n]); my_max 
+my_max = max(df[,n]); my_max 
 
-my_df$foldx_scaled = ifelse(my_df[,n] < 0
+df$foldx_scaled = ifelse(df[,n] < 0
-                            , my_df[,n]/abs(my_min)
+                         , df[,n]/abs(my_min)
-                            , my_df[,n]/my_max) 
+                         , df[,n]/my_max) 
 # sanity check
-my_min = min(my_df$foldx_scaled); my_min 
+my_min = min(df$foldx_scaled); my_min 
-my_max = max(my_df$foldx_scaled); my_max
+my_max = max(df$foldx_scaled); my_max
 
 if (my_min == -1 && my_max == 1){
   cat("\nPASS: foldx ddg successfully scaled b/w -1 and 1"
@@ -67,9 +65,9 @@ if (my_min == -1 && my_max == 1){
 # adding foldx outcome category
 # ddg<0 = "Stabilising" (-ve)
 #------------------------------
-c1 = table(my_df$ddg < 0)
+c1 = table(df$ddg < 0)
-my_df$foldx_outcome = ifelse(my_df$ddg < 0, "Stabilising", "Destabilising")
+df$foldx_outcome = ifelse(df$ddg < 0, "Stabilising", "Destabilising")
-c2 = table(my_df$ddg < 0)
+c2 = table(df$ddg < 0)
 
 if ( all(c1 == c2) ){
   cat("\nPASS: foldx outcome successfully created")
@@ -83,19 +81,19 @@ if ( all(c1 == c2) ){
 #==================================
 
 # check for duplicate mutations
-if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformation)){
+if ( length(unique(df$mutationinformation)) != length(df$mutationinformation)){
   cat(paste0("\nCAUTION:", " Duplicate mutations identified"
              , "\nExtracting these...\n"))
   #cat(my_df[duplicated(my_df$mutationinformation),])
-  dup_muts = my_df[duplicated(my_df$mutationinformation),]
+  dup_muts = df[duplicated(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\n"))
-  my_df_u = my_df[!duplicated(my_df$mutationinformation),]
+  my_df_u = df[!duplicated(df$mutationinformation),]
 }else{
   cat(paste0("\nNo duplicate mutations detected\n"))
-  my_df_u = my_df
+  my_df_u = df
 }
 
 upos = unique(my_df_u$position)
@@ -105,15 +103,14 @@ cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
 #===============================================
 # extract mutations <10 Angstroms and symbol
 #===============================================
-table(my_df_u$ligand_distance<mcsm_lig_cutoff)
+table(my_df_u$ligand_distance<lig_dist_cutoff)
 
-my_df_u_lig = my_df_u[my_df_u$ligand_distance <mcsm_lig_cutoff,]
+my_df_u_lig = my_df_u[my_df_u$ligand_distance <lig_dist_cutoff,]
 
 cat(paste0("There are ", nrow(my_df_u_lig), " sites lying within 10\u212b of the ligand\n"))
 
 # return list of DFs
-
+my_df = df
-#return(list(my_df, my_df_u, my_df_u_lig, dup_muts))
 #df_names = c("my_df", "my_df_u", "my_df_u_lig", "dup_muts")
 all_df = list(my_df, my_df_u, my_df_u_lig, dup_muts)
 #all_df = Map(setNames, all_df, df_names)

scripts/functions/plotting_globals.R

@@ -10,21 +10,21 @@
 # input args: 'drug' and 'gene'
 # output: dir names for input and output files
 
-import_dirs <- function(drug, gene) {
+import_dirs <- function(drug_name, gene_name) {
   
   #============================
   # directories and variables
   #============================
   
   datadir        <<- paste0("~/git/Data/")
-  indir          <<- paste0(datadir, drug, "/input")
+  indir          <<- paste0(datadir, drug_name, "/input")
-  outdir         <<- paste0("~/git/Data/", drug, "/output")
+  outdir         <<- paste0("~/git/Data/", drug_name, "/output")
-  plotdir        <<- paste0("~/git/Data/", drug, "/output/plots")
+  plotdir        <<- paste0("~/git/Data/", drug_name, "/output/plots")
   
-  dr_muts_col    <<- paste0('dr_mutations_', drug)
+  dr_muts_col    <<- paste0('dr_mutations_', drug_name)
-  other_muts_col <<- paste0('other_mutations_', drug)
+  other_muts_col <<- paste0('other_mutations_', drug_name)
   resistance_col <<- "drtype"
-  gene_match     <<- paste0(gene,"_p.")
+  gene_match     <<- paste0(gene_name,"_p.")
   
 }
 
@@ -37,20 +37,17 @@ import_dirs <- function(drug, gene) {
 #==================
 # Angstroms symbol
 #==================
-
 angstroms_symbol <<- "\u212b"
 #cat(paste0("There are ", nrow(my_df_u_lig), " sites lying within 10", angstroms_symbol, " of the ligand\n"))
 
 #===============
 # Delta symbol
 #===============
-
 delta_symbol <<- "\u0394"; delta_symbol
 
 #==========
 # Colours
 #==========
-
 mcsm_red2 <<-  "#ae301e" # most negative
 mcsm_red1 <<-  "#f8766d"
 
@@ -58,3 +55,4 @@ mcsm_mid <<- "white" # middle
 
 mcsm_blue1 <<- "#00bfc4"
 mcsm_blue2 <<- "#007d85" # most positive
+#########################################################

scripts/functions/test_bp.R

@@ -7,6 +7,7 @@ getwd()
 #===========================================
 source("plotting_data.R")
 infile = "/home/tanu/git/Data/streptomycin/output/gid_comb_stab_struc_params.csv"
+
 pd_df = plotting_data(infile)
 my_df       = pd_df[[1]]
 my_df_u     = pd_df[[2]]

scripts/functions/test_combining_dfs_plotting.R

@@ -1,4 +1,4 @@
-# #!/usr/bin/env Rscript
+#!/usr/bin/env Rscript
 
 # working dir and loading libraries
 getwd()
@@ -33,14 +33,20 @@ source("plotting_globals.R")
 source("plotting_data.R")
 source("combining_dfs_plotting.R")
 
-gene = 'gid'
-drug = 'streptomycin'
-
 #---------------------
 # call: import_dirs()
 #---------------------
-import_dirs(drug, gene)
+gene = 'gid'
+drug = 'streptomycin'
 
+import_dirs(drug_name = drug, gene_name = gene)
+
+#-------------------------------
+# test function: plotting_data()
+#-------------------------------
+#============================
+# Input 1: plotting_data()
+#============================
 if (!exists("infile_params") && exists("gene")){
 #if (!is.character(infile_params) && exists("gene")){
   #in_filename_params = paste0(tolower(gene), "_all_params.csv") 
@@ -49,6 +55,13 @@ if (!exists("infile_params") && exists("gene")){
   cat("\nInput file for mcsm comb data not specified, assuming filename: ", infile_params, "\n")
 }
 
+mcsm_comb_data = read.csv(infile_params, header = T)
+pd_df = plotting_data(df = mcsm_comb_data, lig_dist_cutoff = 10)
+my_df_u = pd_df[[2]]
+
+#======================================
+# Input 2: read <gene>_meta data.csv
+#======================================
 if (!exists("infile_metadata") && exists("gene")){
 #if (!is.character(infile_params) && exists("gene")){{
   in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
@@ -56,18 +69,6 @@ if (!exists("infile_metadata") && exists("gene")){
   cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
 }
 
-#============================
-# Input 1: plotting_data()
-#============================
-#---------------------
-# call: plotting_data()
-#---------------------
-pd_df = plotting_data(infile_params)
-my_df       = pd_df[[1]] # this forms one of the input for combining_dfs_plotting()
-
-#======================================
-# Input 2: read <gene>_meta data.csv
-#======================================
 cat("\nReading meta data file:", infile_metadata)
 
 gene_metadata <- read.csv(infile_metadata
@@ -85,3 +86,5 @@ merged_df2_comp   = all_plot_dfs[[3]]
 merged_df3_comp     = all_plot_dfs[[4]]
 merged_df2_lig      = all_plot_dfs[[5]]
 merged_df3_lig      = all_plot_dfs[[6]]
+merged_df2_comp_lig = all_plot_dfs[[7]]
+merged_df3_comp_lig = all_plot_dfs[[8]]

scripts/plotting/Header_TT.R

@@ -7,6 +7,7 @@
 #  install.packages("gplots", dependencies = TRUE)
 #  library(gplots)
 #}
+require("getopt", quietly = TRUE) # cmd parse arguments
 
 if (!require("tidyverse")) {
   install.packages("tidyverse", dependencies = TRUE)

scripts/plotting/logo_combined.R

@@ -10,15 +10,66 @@ setwd("~/git/LSHTM_analysis/scripts/plotting")
 getwd()
 
 source("Header_TT.R")
-#library(ggplot2)
+source("../functions/plotting_globals.R")
-#library(data.table)
+source("../functions/plotting_data.R")
-#library(dplyr)
+source("../functions/combining_dfs_plotting.R")
+###########################################################
+# command line args
+#********************
+drug = 'streptomycin'
+gene = 'gid'
 
 #===========
 # input
 #===========
-source("combining_dfs_plotting.R")
+#---------------------
+# call: import_dirs()
+#---------------------
+import_dirs(drug, gene)
 
+#---------------------------
+# call: plotting_data()
+#---------------------------
+if (!exists("infile_params") && exists("gene")){
+  #if (!is.character(infile_params) && exists("gene")){
+  #in_filename_params = paste0(tolower(gene), "_all_params.csv") 
+  in_filename_params = paste0(tolower(gene), "_comb_afor.csv") # part combined for gid
+  infile_params = paste0(outdir, "/", in_filename_params)
+  cat("\nInput file for mcsm comb data not specified, assuming filename: ", infile_params, "\n")
+}
+
+# Input 1: read <gene>_comb_afor.csv
+pd_df = plotting_data(infile_params)
+my_df_u       = pd_df[[1]] # this forms one of the input for combining_dfs_plotting()
+
+#--------------------------------
+# call: combining_dfs_plotting()
+#--------------------------------
+if (!exists("infile_metadata") && exists("gene")){
+  #if (!is.character(infile_params) && exists("gene")){{
+  in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
+  infile_metadata = paste0(outdir, "/", in_filename_metadata)
+  cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
+}
+
+# Input 2: read <gene>_meta data.csv
+cat("\nReading meta data file:", infile_metadata)
+
+gene_metadata <- read.csv(infile_metadata
+                          , stringsAsFactors = F
+                          , header = T)
+
+all_plot_dfs = combining_dfs_plotting(my_df_u
+                                      , gene_metadata
+                                      , lig_dist_colname = 'ligand_distance'
+                                      , lig_dist_cutoff = 10)
+
+#merged_df2        = all_plot_dfs[[1]]
+merged_df3        = all_plot_dfs[[2]]
+#merged_df2_comp   = all_plot_dfs[[3]]
+#merged_df3_comp   = all_plot_dfs[[4]]
+#merged_df2_lig    = all_plot_dfs[[5]]
+#merged_df3_lig    = all_plot_dfs[[6]]
 #===========
 # output
 #===========
@@ -32,12 +83,6 @@ plot_logo_combined_labelled  = paste0(plotdir,"/", logo_combined_labelled)
 # REASSIGNMENT
 my_df = merged_df3 
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-# clear excess variables
-rm(merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig
-   , merged_df3_comp, merged_df3_comp_lig
-   , my_df_u, my_df_u_lig, merged_df3_lig)
-
 colnames(my_df)
 str(my_df)
 
@@ -167,7 +212,7 @@ p3 = p2 +
         #, legend.title = element_blank()
         , legend.title = element_text("Amino acid properties", size = 20)
         , legend.text = element_text(size = 20)
-        , axis.text.x = element_text(size = 20, angle = 90)
+        , axis.text.x = element_text(size = 16, angle = 90)
         , axis.text.y = element_blank()
         , axis.title.y = element_blank()
         , axis.title.x = element_text(size = 22))+
@@ -237,7 +282,7 @@ position_or = as.numeric(colnames(wide_df_or))
 #============================================  
 # custom height (OR) logo plot: yayy works
 logo_or = ggseqlogo(wide_df_or, method="custom", seq_type="aa") + ylab("my custom height") +
-  theme(axis.text.x = element_text(size = 16
+  theme(axis.text.x = element_text(size = 15
                                     , angle = 90
                                     , hjust = 1
                                     , vjust = 0.4)

scripts/plotting/logo_multiple_muts.R

@@ -10,14 +10,66 @@ setwd("~/git/LSHTM_analysis/scripts/plotting")
 getwd()
 
 source("Header_TT.R")
-#library(ggplot2)
+source("../functions/plotting_globals.R")
-#library(data.table)
+source("../functions/plotting_data.R")
-#library(dplyr)
+source("../functions/combining_dfs_plotting.R")
+###########################################################
+# command line args
+#********************
+drug = 'streptomycin'
+gene = 'gid'
 
 #===========
 # input
 #===========
-source("combining_dfs_plotting.R")
+#---------------------
+# call: import_dirs()
+#---------------------
+import_dirs(drug, gene)
+
+#---------------------------
+# call: plotting_data()
+#---------------------------
+if (!exists("infile_params") && exists("gene")){
+  #if (!is.character(infile_params) && exists("gene")){
+  #in_filename_params = paste0(tolower(gene), "_all_params.csv") 
+  in_filename_params = paste0(tolower(gene), "_comb_afor.csv") # part combined for gid
+  infile_params = paste0(outdir, "/", in_filename_params)
+  cat("\nInput file for mcsm comb data not specified, assuming filename: ", infile_params, "\n")
+}
+
+# Input 1: read <gene>_comb_afor.csv
+pd_df = plotting_data(infile_params)
+my_df_u       = pd_df[[1]] # this forms one of the input for combining_dfs_plotting()
+
+#--------------------------------
+# call: combining_dfs_plotting()
+#--------------------------------
+if (!exists("infile_metadata") && exists("gene")){
+  #if (!is.character(infile_params) && exists("gene")){{
+  in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
+  infile_metadata = paste0(outdir, "/", in_filename_metadata)
+  cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
+}
+
+# Input 2: read <gene>_meta data.csv
+cat("\nReading meta data file:", infile_metadata)
+
+gene_metadata <- read.csv(infile_metadata
+                          , stringsAsFactors = F
+                          , header = T)
+
+all_plot_dfs = combining_dfs_plotting(my_df_u
+                                      , gene_metadata
+                                      , lig_dist_colname = 'ligand_distance'
+                                      , lig_dist_cutoff = 10)
+
+#merged_df2        = all_plot_dfs[[1]]
+merged_df3        = all_plot_dfs[[2]]
+#merged_df2_comp   = all_plot_dfs[[3]]
+#merged_df3_comp   = all_plot_dfs[[4]]
+#merged_df2_lig    = all_plot_dfs[[5]]
+#merged_df3_lig    = all_plot_dfs[[6]]
 
 #===========
 # output
@@ -32,12 +84,6 @@ plot_logo_multiple_muts = paste0(plotdir,"/", logo_multiple_muts)
 # REASSIGNMENT
 my_df = merged_df3 
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-# clear excess variables
-rm(merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig
-   , merged_df3_comp, merged_df3_comp_lig
-   , my_df_u, my_df_u_lig, merged_df3_lig)
-
 colnames(my_df)
 str(my_df)
 
@@ -117,7 +163,7 @@ p0
 p1 = p0 + theme(legend.position = "none"
                 , legend.title = element_blank()
                 , legend.text = element_text(size = 20)
-                , axis.text.x = element_text(size = 20, angle = 90)
+                , axis.text.x = element_text(size = 17, angle = 90)
                 , axis.text.y = element_blank())
 p1
 
@@ -138,7 +184,6 @@ rownames(tab_wt)
 
 #**************
 # Plot 2: wild_type logo
-
 #**************
 # sanity check: MUST BE TRUE
 
@@ -165,7 +210,7 @@ p3 = p2 +
         #, legend.title = element_blank()
         , legend.title = element_text("Amino acid properties", size = 20)
         , legend.text = element_text(size = 20)
-        , axis.text.x = element_text(size = 20, angle = 90)
+        , axis.text.x = element_text(size = 17, angle = 90)
         , axis.text.y = element_blank()
         , axis.title.x = element_text(size = 22))+
   

scripts/plotting/logo_plot.R

@@ -15,9 +15,36 @@ source("../functions/combining_dfs_plotting.R")
 ###########################################################
 # command line args
 #********************
-drug = 'streptomycin'
+#drug = 'streptomycin'
-gene = 'gid'
+#gene = 'gid'
+#********************
+# !!!FUTURE TODO!!!
+# Can pass additional params of output/plot dir by user. 
+# Not strictly required for my workflow  since it is optimised
+# to have a streamlined input/output flow without filename worries.
+#********************
+spec = matrix(c(
+  "drug"       , "d",  1, "character",
+  "gene"       , "g",  1, "character",
+  "data_file1" , "fa", 2, "character",
+  "data_file2" , "fb", 2, "character" 
+), byrow = TRUE, ncol = 4)
 
+opt = getopt(spec)
+
+#FIXME: detect if script running from cmd, then set these
+drug            = opt$drug
+gene            = opt$gene
+infile_params   = opt$data_file1
+infile_metadata = opt$data_file2
+
+# hardcoding when not using cmd
+#drug = "streptomycin"
+#gene = "gid"
+
+if(is.null(drug)|is.null(gene)) {
+  stop("Missing arguments: --drug and --gene must both be specified (case-sensitive)")
+}
 #===========
 # input
 #===========
@@ -29,8 +56,8 @@ import_dirs(drug, gene)
 #---------------------------
 # call: plotting_data()
 #---------------------------
-if (!exists("infile_params") && exists("gene")){
+#if (!exists("infile_params") && exists("gene")){
-  #if (!is.character(infile_params) && exists("gene")){
+if (!is.character(infile_params) && exists("gene")){
   #in_filename_params = paste0(tolower(gene), "_all_params.csv") 
   in_filename_params = paste0(tolower(gene), "_comb_afor.csv") # part combined for gid
   infile_params = paste0(outdir, "/", in_filename_params)
@@ -38,14 +65,15 @@ if (!exists("infile_params") && exists("gene")){
 }
 
 # Input 1: read <gene>_comb_afor.csv
-pd_df = plotting_data(infile_params)
+my_df = read.csv(infile_params, header = T)
+pd_df = plotting_data(my_df)
 my_df_u       = pd_df[[1]] # this forms one of the input for combining_dfs_plotting()
 
 #--------------------------------
 # call: combining_dfs_plotting()
 #--------------------------------
-if (!exists("infile_metadata") && exists("gene")){
+#if (!exists("infile_metadata") && exists("gene")){
-  #if (!is.character(infile_params) && exists("gene")){{
+if (!is.character(infile_params) && exists("gene")){
   in_filename_metadata = paste0(tolower(gene), "_metadata.csv") # part combined for gid
   infile_metadata = paste0(outdir, "/", in_filename_metadata)
   cat("\nInput file for gene metadata not specified, assuming filename: ", infile_metadata, "\n")
@@ -63,7 +91,7 @@ all_plot_dfs = combining_dfs_plotting(my_df_u
                                       , lig_dist_colname = 'ligand_distance'
                                       , lig_dist_cutoff = 10)
 
-merged_df2        = all_plot_dfs[[1]]
+#merged_df2        = all_plot_dfs[[1]]
 merged_df3        = all_plot_dfs[[2]]
 #merged_df2_comp   = all_plot_dfs[[3]]
 #merged_df3_comp   = all_plot_dfs[[4]]
@@ -146,6 +174,7 @@ wide_df_or <- logo_data_or %>% spread(position, or_mychisq, fill = 0.0)
 
 wide_df_or = as.matrix(wide_df_or)
 rownames(wide_df_or) = wide_df_or[,1]
+dim(wide_df_or)
 wide_df_or = wide_df_or[,-1]
 str(wide_df_or)