#!/usr/bin/env Rscript       
#source("~/git/LSHTM_analysis/config/alr.R")
source("~/git/LSHTM_analysis/config/embb.R")
#source("~/git/LSHTM_analysis/config/katg.R")
#source("~/git/LSHTM_analysis/config/gid.R")
#source("~/git/LSHTM_analysis/config/pnca.R")
#source("~/git/LSHTM_analysis/config/rpob.R")

# get plottting dfs 
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")

source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
#=======
# output
#=======
outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/")
outdir_stats = paste0(outdir_images,"stats/") 

###################################################################
# FIXME: ADD distance to NA when SP replies

geneL_normal  = c("pnca")
geneL_na      = c("gid", "rpob")
geneL_ppi2    = c("alr", "embb", "katg", "rpob")

# LigDist_colname # from globals used
# ppi2Dist_colname #from globals used 
# naDist_colname #from globals used

df3 = merged_df3

# Add adjusted P-values
df3$p_adj_fdr = p.adjust(df3$pval_fisher, method = "fdr")
df3$signif_fdr = df3$p_adj_fdr
df3 = dplyr::mutate(df3
                    , signif_fdr = case_when(signif_fdr == 0.05 ~ "."
                                             , signif_fdr <=0.0001 ~ '****'
                                             , signif_fdr <=0.001 ~ '***'
                                             , signif_fdr <=0.01 ~ '**'
                                             , signif_fdr <0.05 ~ '*'
                                             , TRUE ~ 'ns'))




####################################
# Appendix: ligand affinity
####################################
df_lig = df3[df3[[LigDist_colname]]<DistCutOff,]


cols_to_output_lig = c("mutationinformation"
                   , "position"
                   , LigDist_colname
                   , "ligand_affinity_change"
                   , "ligand_outcome"
                   , "mmcsm_lig"
                   , "mmcsm_lig_outcome"
                   , "or_mychisq"
                   , "p_adj_fdr"
                   , "signif_fdr")

# counting

Out_df_lig = df_lig[, cols_to_output_lig]
Out_df_ligS = Out_df_lig[order(Out_df_lig$or_mychisq, decreasing = T), ]

delta_symbol = "\u0394"; delta_symbol

Out_df_ligS$or_mychisq = round(Out_df_ligS$or_mychisq,2)
Out_df_ligS$p_adj_fdr = round(Out_df_ligS$p_adj_fdr,2)
Out_df_ligS

colsNames_to_output_lig = c("Mutation"
                   , "position"
                   , paste0("Lig-Dist (", angstroms_symbol, ")")
                   , "mCSM-ligand affinity"
                   , "mCSM ligand_outcome"
                   , "mmCSM-ligand affinity"
                   , "mmCSM ligand_outcome"
                   , "Odds Ratio"
                   , "Adj P-value"
                   , "P-value significance")

colnames(Out_df_ligS) = colsNames_to_output_lig
Out_df_ligS
#--------------------
# write output file: KS test within grpup
#----------------------
Out_ligT = paste0(outdir_stats
                    , tolower(gene)
                    , "_lig_muts.csv")

cat("Output of Ligand muts:", Out_ligT )
write.csv(Out_df_ligS, Out_ligT, row.names = FALSE)

########################################################################
####################################
# Appendix: PPi2 affinity
####################################

df_ppi2 = df3[df3[[ppi2Dist_colname]]<DistCutOff,]


cols_to_output_ppi2 = c("mutationinformation"
                        , "position"
                        , ppi2Dist_colname
                        , "mcsm_ppi2_affinity"
                        , "mcsm_ppi2_outcome"
                        , "or_mychisq"
                        , "p_adj_fdr"
                        , "signif_fdr")

# extract output cols
Out_df_ppi2 = df_ppi2[, cols_to_output_ppi2]
Out_df_ppi2S = Out_df_ppi2[order(Out_df_ppi2$or_mychisq, decreasing = T), ]

delta_symbol = "\u0394"; delta_symbol

Out_df_ppi2S$or_mychisq = round(Out_df_ppi2S$or_mychisq,2)
Out_df_ppi2S$p_adj_fdr = round(Out_df_ppi2S$p_adj_fdr,2)
Out_df_ppi2S

colsNames_to_output_ppi2 = c("Mutation"
                             , "position"
                             , paste0("PPI2-Dist (", angstroms_symbol, ")")
                             , paste0("mCSM-PPI2 (", delta_symbol, ")")
                             , "mCSM-PPI2 outcome"
                             , "Odds Ratio"
                             , "Adj P-value"
                             , "P-value significance")

colnames(Out_df_ppi2S) = colsNames_to_output_ppi2
Out_df_ppi2S
#--------------------
# write output file: KS test within grpup
#----------------------
Out_ppi2T = paste0(outdir_stats
                   , tolower(gene)
                   , "_ppi2_muts.csv")

cat("Output of PPI2 muts:", Out_ppi2T )
write.csv(Out_df_ppi2S, Out_ppi2T, row.names = FALSE)