829 lines
31 KiB
R
829 lines
31 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: Script to format data for dm om plots:
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# generating WF and LF data for each of the parameters:
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# duet, mcsm-lig, foldx, deepddg, dynamut2, mcsm-na, mcsm-ppi2, encom, dynamut..etc
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# Called by get_plotting_dfs.R
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##################################################################
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# from plotting_globals.R
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# DistCutOff, LigDist_colname, ppi2Dist_colname, naDist_colname
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#gene
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dm_om_wf_lf_data <- function(df
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, gene # from globals
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, colnames_to_extract
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#, LigDist_colname # from globals used
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#, ppi2Dist_colname #from globals used
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#, naDist_colname #from globals used
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, snp_colname = "mutationinformation"
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, aa_pos_colname = "position"
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, mut_colname = "mutation"
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, mut_info_colname = "dst_mode"
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, mut_info_label_colname = "mutation_info_labels"
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, categ_cols_to_factor){
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df = as.data.frame(df)
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df$maf2 = log10(df$maf) # can't see otherwise
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sum(is.na(df$maf2))
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# Initialise the required dfs based on gene name
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#geneL_normal = c("pnca")
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#geneL_na = c("gid", "rpob")
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#geneL_ppi2 = c("alr", "embb", "katg", "rpob")
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#ADDED: IMPORTANT for rpob to be in both to make sure all data is returned
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geneL_normal = c("pnca")
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geneL_both = c("rpob")
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geneL_ppi2 = c("alr", "embb", "katg")
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geneL_na = c("gid")
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# common_dfs
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common_dfsL = list(
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wf_duet = data.frame()
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, lf_duet = data.frame()
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, wf_mcsm_lig = data.frame()
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, lf_mcsm_lig = data.frame()
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, wf_mmcsm_lig2 = data.frame() # NEW
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, lf_mmcsm_lig2 = data.frame() # NEW
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, wf_foldx = data.frame()
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, lf_foldx = data.frame()
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, wf_deepddg = data.frame()
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, lf_deepddg = data.frame()
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, wf_dynamut2 = data.frame()
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, lf_dynamut2 = data.frame()
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, wf_consurf = data.frame()
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, lf_consurf = data.frame()
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, wf_snap2 = data.frame()
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, lf_snap2 = data.frame()
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, wf_dist_gen = data.frame() # NEW
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, lf_dist_gen = data.frame() # NEW
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)
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# additional dfs
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if (tolower(gene)%in%geneL_normal){
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wf_lf_dataL = common_dfsL
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}
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if (tolower(gene)%in%geneL_ppi2){
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additional_dfL = list(
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wf_mcsm_ppi2 = data.frame()
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, lf_mcsm_ppi2 = data.frame()
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)
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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if (tolower(gene)%in%geneL_na){
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additional_dfL = list(
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wf_mcsm_na = data.frame()
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, lf_mcsm_na = data.frame()
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)
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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if (tolower(gene)%in%geneL_both){
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additional_dfL = list(
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wf_mcsm_ppi2 = data.frame(),
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lf_mcsm_ppi2 = data.frame(),
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wf_mcsm_na = data.frame(),
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lf_mcsm_na = data.frame()
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)
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wf_lf_dataL = c(common_dfsL, additional_dfL)
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}
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cat("\nInitializing an empty list of length:"
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, length(wf_lf_dataL))
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#=======================================================================
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# display names
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stability_suffix <- paste0(delta_symbol, delta_symbol, "G")
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duet_dn = paste0("DUET ", stability_suffix); duet_dn
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foldx_dn = paste0("FoldX ", stability_suffix); foldx_dn
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deepddg_dn = paste0("Deepddg " , stability_suffix); deepddg_dn
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dynamut2_dn = paste0("Dynamut2 " , stability_suffix); dynamut2_dn
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consurf_dn = "ConSurf"
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snap2_dn = "SNAP2"
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provean_dn = "PROVEAN"
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or_dn = "Log10(OR)"
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pval_dn = "-Log10(P)"
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maf2_dn = "Log10(MAF)"
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asa_dn = "ASA"
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rsa_dn = "RSA"
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rd_dn = "RD"
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kd_dn = "KD"
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lig_dist_dn = paste0("Lig Dist(", angstroms_symbol, ")"); lig_dist_dn
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mcsm_lig_dn = paste0("mCSM-lig"); mcsm_lig_dn
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mmcsm_lig_dn2 = paste0("mmCSM-lig"); mmcsm_lig_dn2
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na_dist_dn = paste0("Dist to NA (", angstroms_symbol, ")"); na_dist_dn
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mcsm_na_dn = paste0("mCSM-NA ", stability_suffix); mcsm_na_dn
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ppi2_dist_dn = paste0("PPI Dist(", angstroms_symbol, ")"); ppi2_dist_dn
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mcsm_ppi2_dn = paste0("mCSM-PPI2 ", stability_suffix); mcsm_ppi2_dn
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#=======================================================================
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if(missing(categ_cols_to_factor)){
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categ_cols_to_factor = grep( "_outcome|_info", colnames(df) )
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}else{
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categ_cols_to_factor = categ_cols_to_factor
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}
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#fact_cols = colnames(comb_df_s)[grepl( "_outcome|_info", colnames(comb_df_s) )]
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fact_cols = colnames(df)[categ_cols_to_factor]
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if (any(lapply(df[, fact_cols], class) == "character")){
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cat("\nChanging", length(categ_cols_to_factor), "cols to factor")
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df[, fact_cols] <- lapply(df[, fact_cols], as.factor)
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if (all(lapply(df[, fact_cols], class) == "factor")){
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cat("\nSuccessful: cols changed to factor")
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}
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}else{
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cat("\nRequested cols aready factors")
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}
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cat("\ncols changed to factor are:\n", colnames(df)[categ_cols_to_factor] )
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#=======================================================================
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if (missing(colnames_to_extract)){
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# NOTE: these vars are from globals
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#LigDist_colname, ppi2Dist_colname, naDist_colname
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common_colnames = c(snp_colname
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, mut_colname , "dst_mode" , mut_info_label_colname
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, aa_pos_colname
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, "duet_stability_change" , "duet_scaled" , "duet_outcome"
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, "ddg_foldx" , "foldx_scaled" , "foldx_outcome"
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, "deepddg" , "deepddg_scaled" , "deepddg_outcome"
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, "ddg_dynamut2" , "ddg_dynamut2_scaled" , "ddg_dynamut2_outcome"
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, "consurf_score" , "consurf_scaled" , "consurf_outcome" , "consurf_colour_rev"
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, "snap2_score" , "snap2_scaled" , "snap2_outcome"
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, "provean_score" , "provean_scaled" , "provean_outcome"
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, "log10_or_mychisq" , "neglog_pval_fisher" , "maf2"
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, "asa" , "rsa" , "rd_values" , "kd_values"
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, "mmcsm_lig" , "mmcsm_lig_scaled" , "mmcsm_lig_outcome"
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, "ligand_affinity_change", "affinity_scaled" , "ligand_outcome" , LigDist_colname
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)
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display_common_colnames = c(snp_colname
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, mut_colname
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, "dst_mode" , mut_info_label_colname
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, aa_pos_colname
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, "duet_stability_change" , duet_dn , "duet_outcome"
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, "ddg_foldx" , foldx_dn , "foldx_outcome"
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, "deepddg" , deepddg_dn , "deepddg_outcome"
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, "ddg_dynamut2" , dynamut2_dn , "ddg_dynamut2_outcome"
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, consurf_dn , "consurf_scaled" , "consurf_outcome" , "consurf_colour_rev"
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, snap2_dn , "snap2_scaled" , "snap2_outcome"
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, provean_dn , "provean_scaled" , "provean_outcome"
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, or_dn , pval_dn , maf2_dn
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, asa_dn , rsa_dn , rd_dn , kd_dn
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, "mmcsm_lig" , mmcsm_lig_dn2 , "mmcsm_lig_outcome"
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, "ligand_affinity_change", mcsm_lig_dn , "ligand_outcome" , lig_dist_dn
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)
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if (length(common_colnames) == length(display_common_colnames)){
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cat("\nLength match: Proceeding to extracting end cols")
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}else{
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stop("Abort: Length mismatch: b/w ncols to extract and disply name")
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}
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# ordering is important!
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# static_cols_end = c(lig_dist_dn
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# , "ASA"
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# , "RSA"
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# , "RD"
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# , "KD"
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# , "Log10(MAF)"
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# #, "Log10(OR)"
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# #, "-Log(P)"
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# )
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static_cols_end_common = c(lig_dist_dn, "Log10(MAF)"); static_cols_end_common
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if (tolower(gene)%in%geneL_normal){
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colnames_to_extract = c(common_colnames)
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display_colnames = c(display_common_colnames)
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comb_df_sl = df[, colnames_to_extract]
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# Rename cols: display names
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colnames(comb_df_sl) = display_colnames
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#colnames(comb_df)[colnames(comb_df)%in%colnames_to_extract] <- display_colnames
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static_cols_end = static_cols_end_common
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cat("\nend colnames for gene:", static_cols_end)
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}
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if (tolower(gene)%in%geneL_ppi2){
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colnames_to_extract = c(common_colnames, "mcsm_ppi2_affinity" ,"mcsm_ppi2_scaled" , "mcsm_ppi2_outcome" , ppi2Dist_colname)
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display_colnames = c(display_common_colnames,"mcsm_ppi2_affinity", mcsm_ppi2_dn , "mcsm_ppi2_outcome" , ppi2_dist_dn )
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comb_df_sl = df[, colnames_to_extract]
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# Rename cols: display names
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colnames(comb_df_sl) = display_colnames
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# Affinity filtered data: mcsm-ppi2 --> ppi2Dist_colname
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comb_df_sl_ppi2 = comb_df_sl[comb_df_sl[[ppi2_dist_dn]]<DistCutOff,]
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# ordering is important!
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static_cols_end = c(ppi2_dist_dn, static_cols_end_common)
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cat("\nend colnames for gene:", static_cols_end)
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}
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if (tolower(gene)%in%geneL_na){
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colnames_to_extract = c(common_colnames ,"mcsm_na_affinity" , "mcsm_na_scaled" , "mcsm_na_outcome" , naDist_colname)
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display_colnames = c(display_common_colnames, "mcsm_na_affinity" , mcsm_na_dn , "mcsm_na_outcome" , na_dist_dn)
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comb_df_sl = df[, colnames_to_extract]
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# Rename cols: display names
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colnames(comb_df_sl) = display_colnames
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# Affinity filtered data: mcsm-na --> naDist_colname
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comb_df_sl_na = comb_df_sl[comb_df_sl[[na_dist_dn]]<DistCutOff,]
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# ordering is important!
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static_cols_end = c(na_dist_dn, static_cols_end_common)
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cat("\nend colnames for gene:", static_cols_end)
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}
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if (tolower(gene)%in%geneL_both){
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colnames_to_extract = c(
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common_colnames,
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"mcsm_ppi2_affinity" ,
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"mcsm_ppi2_scaled" ,
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"mcsm_ppi2_outcome" ,
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ppi2Dist_colname,
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"mcsm_na_affinity" ,
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"mcsm_na_scaled" ,
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"mcsm_na_outcome" ,
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naDist_colname
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)
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display_colnames = c(
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display_common_colnames,
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"mcsm_ppi2_affinity",
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mcsm_ppi2_dn,
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"mcsm_ppi2_outcome",
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ppi2_dist_dn,
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"mcsm_na_affinity",
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mcsm_na_dn,
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"mcsm_na_outcome",
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na_dist_dn
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)
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comb_df_sl = df[, colnames_to_extract]
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colnames(comb_df_sl) = display_colnames
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comb_df_sl_ppi2 = comb_df_sl[comb_df_sl[[ppi2_dist_dn]]<DistCutOff,]
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comb_df_sl_na = comb_df_sl[comb_df_sl[[na_dist_dn]]<DistCutOff,]
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static_cols_end = c(na_dist_dn, static_cols_end_common)
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}
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# Affinity filtered data: mcsm-lig: COMMON for all genes, mcsm-lig --> LigDist_colname
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comb_df_sl_lig = comb_df_sl[comb_df_sl[[lig_dist_dn]]<DistCutOff,]
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}
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#======================
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# Selecting dfs
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# with appropriate cols
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#=======================
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static_cols_start = c(snp_colname
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, aa_pos_colname
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, mut_colname
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, mut_info_label_colname)
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# static_cols_end
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cat("\nEnd colnames for gene:", static_cols_end)
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#########################################################################
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#==============
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# Distance and genomics
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#==============
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# WF data: dist + genomics
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cols_to_select_dist_gen = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_dist_gen = comb_df_sl[, cols_to_select_dist_gen]; head(wf_dist_gen)
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_dist_gen = cols_to_select_dist_gen[1: (length(static_cols_start) + 1)]; pivot_cols_dist_gen
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expected_rows_lf = nrow(wf_dist_gen) * (length(wf_dist_gen) - length(pivot_cols_dist_gen))
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expected_rows_lf
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# LF dist and genomics
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lf_dist_gen = tidyr::gather(wf_dist_gen
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, key = param_type
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, value = param_value
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, all_of(duet_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_dist_gen) == expected_rows_lf){
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cat("\nPASS: long format data created for Distance and Genomics")
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}else{
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cat("\nFAIL: long format data could not be created for Distance and Genomics")
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quit()
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}
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# DROP duet cols
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drop_cols = c(duet_dn, "duet_outcome"); drop_cols
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table(lf_dist_gen$param_type)
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lf_dist_gen = lf_dist_gen[!lf_dist_gen$param_type%in%drop_cols,]
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lf_dist_gen$param_type = factor(lf_dist_gen$param_type)
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table(lf_dist_gen$param_type)
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# NEW columns [outcome and outcome colname]
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lf_dist_gen$outcome_colname = mut_info_colname
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lf_dist_gen$outcome = lf_dist_gen[[mut_info_label_colname]]
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head(lf_dist_gen)
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wf_dist_gen = subset(wf_dist_gen, select = !(names(wf_dist_gen) %in% drop_cols))
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colnames(wf_dist_gen)
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colnames(lf_dist_gen)
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# Assign them to the output list
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wf_lf_dataL[['wf_dist_gen']] = wf_dist_gen
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wf_lf_dataL[['lf_dist_gen']] = lf_dist_gen
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##########################################################
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#==============
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# DUET
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#==============
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# WF data: duet
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cols_to_select_duet = c(static_cols_start, c("duet_outcome", duet_dn), static_cols_end)
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wf_duet = comb_df_sl[, cols_to_select_duet]
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#pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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pivot_cols_duet = cols_to_select_duet[1: (length(static_cols_start) + 1)]; pivot_cols_duet
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expected_rows_lf = nrow(wf_duet) * (length(wf_duet) - length(pivot_cols_duet))
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expected_rows_lf
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# LF data: duet
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lf_duet = tidyr::gather(wf_duet
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, key = param_type
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, value = param_value
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, all_of(duet_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_duet) == expected_rows_lf){
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cat("\nPASS: long format data created for ", duet_dn)
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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table(lf_duet$param_type)
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# NEW columns [outcome and outcome colname]
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lf_duet$outcome_colname = "duet_outcome"
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lf_duet$outcome = lf_duet$duet_outcome
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# DROP static cols
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lf_duet = lf_duet[!lf_duet$param_type%in%c(static_cols_end),]
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lf_duet$param_type = factor(lf_duet$param_type)
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table(lf_duet$param_type); colnames(lf_duet)
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# Assign them to the output list
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wf_lf_dataL[['wf_duet']] = wf_duet
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wf_lf_dataL[['lf_duet']] = lf_duet
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############################################################################
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#==============
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# FoldX
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#==============
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# WF data: Foldx
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cols_to_select_foldx= c(static_cols_start, c("foldx_outcome", foldx_dn), static_cols_end)
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wf_foldx = comb_df_sl[, cols_to_select_foldx]
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pivot_cols_foldx = cols_to_select_foldx[1: (length(static_cols_start) + 1)]; pivot_cols_foldx
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expected_rows_lf = nrow(wf_foldx) * (length(wf_foldx) - length(pivot_cols_foldx))
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expected_rows_lf
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# LF data: Foldx
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lf_foldx = gather(wf_foldx
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, key = param_type
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, value = param_value
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, all_of(foldx_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_foldx) == expected_rows_lf){
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cat("\nPASS: long format data created for ", foldx_dn)
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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# NEW column
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lf_foldx$outcome_colname = "foldx_outcome"
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lf_foldx$outcome = lf_foldx$foldx_outcome
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|
|
# DROP static cols
|
|
lf_foldx = lf_foldx[!lf_foldx$param_type%in%c(static_cols_end),]
|
|
lf_foldx$param_type = factor(lf_foldx$param_type)
|
|
table(lf_foldx$param_type); colnames(lf_foldx)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_foldx']] = wf_foldx
|
|
wf_lf_dataL[['lf_foldx']] = lf_foldx
|
|
|
|
############################################################################
|
|
#==============
|
|
# Deepddg
|
|
#==============
|
|
# WF data: deepddg
|
|
cols_to_select_deepddg = c(static_cols_start, c("deepddg_outcome", deepddg_dn), static_cols_end)
|
|
wf_deepddg = comb_df_sl[, cols_to_select_deepddg]
|
|
|
|
pivot_cols_deepddg = cols_to_select_deepddg[1: (length(static_cols_start) + 1)]; pivot_cols_deepddg
|
|
expected_rows_lf = nrow(wf_deepddg) * (length(wf_deepddg) - length(pivot_cols_deepddg))
|
|
expected_rows_lf
|
|
|
|
# LF data: Deepddg
|
|
lf_deepddg = gather(wf_deepddg
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(deepddg_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_deepddg) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", deepddg_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_deepddg$outcome_colname = "deepddg_outcome"
|
|
lf_deepddg$outcome = lf_deepddg$deepddg_outcome
|
|
|
|
# DROP static cols
|
|
lf_deepddg = lf_deepddg[!lf_deepddg$param_type%in%c(static_cols_end),]
|
|
lf_deepddg$param_type = factor(lf_deepddg$param_type)
|
|
table(lf_deepddg$param_type); colnames(lf_deepddg)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_deepddg']] = wf_deepddg
|
|
wf_lf_dataL[['lf_deepddg']] = lf_deepddg
|
|
############################################################################
|
|
#==============
|
|
# Dynamut2: LF
|
|
#==============
|
|
# WF data: dynamut2
|
|
cols_to_select_dynamut2 = c(static_cols_start, c("ddg_dynamut2_outcome", dynamut2_dn), static_cols_end)
|
|
wf_dynamut2 = comb_df_sl[, cols_to_select_dynamut2]
|
|
|
|
pivot_cols_dynamut2 = cols_to_select_dynamut2[1: (length(static_cols_start) + 1)]; pivot_cols_dynamut2
|
|
expected_rows_lf = nrow(wf_dynamut2) * (length(wf_dynamut2) - length(pivot_cols_dynamut2))
|
|
expected_rows_lf
|
|
|
|
# LF data: dynamut2
|
|
lf_dynamut2 = gather(wf_dynamut2
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(dynamut2_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_dynamut2) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", dynamut2_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_dynamut2$outcome_colname = "ddg_dynamut2_outcome"
|
|
lf_dynamut2$outcome = lf_dynamut2$ddg_dynamut2_outcome
|
|
|
|
# DROP static cols
|
|
lf_dynamut2 = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_cols_end),]
|
|
lf_dynamut2$param_type = factor(lf_dynamut2$param_type)
|
|
table(lf_dynamut2$param_type); colnames(lf_dynamut2)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_dynamut2']] = wf_dynamut2
|
|
wf_lf_dataL[['lf_dynamut2']] = lf_dynamut2
|
|
|
|
######################################################################################
|
|
#==================
|
|
# Consurf: LF
|
|
#https://consurf.tau.ac.il/overview.php
|
|
# consurf_score:
|
|
# <0 (below average): slowly evolving i.e CONSERVED
|
|
# >0 (above average): rapidly evolving, i.e VARIABLE
|
|
#table(df$consurf_colour_rev)
|
|
# TODO
|
|
#1--> "most_variable", 2--> "", 3-->"", 4-->""
|
|
#5-->"", 6-->"", 7-->"", 8-->"", 9-->"most_conserved"
|
|
#====================
|
|
# WF data: consurf
|
|
cols_to_select_consurf = c(static_cols_start, c("consurf_outcome", consurf_dn), static_cols_end)
|
|
wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
|
|
|
pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start) + 1)]; pivot_cols_consurf
|
|
expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
|
expected_rows_lf
|
|
|
|
# when outcome didn't exist
|
|
#cols_to_select_consurf = c(static_cols_start, c(consurf_dn), static_cols_end)
|
|
#wf_consurf = comb_df_sl[, cols_to_select_consurf]
|
|
#
|
|
# pivot_cols_consurf = cols_to_select_consurf[1: (length(static_cols_start))]; pivot_cols_consurf
|
|
# expected_rows_lf = nrow(wf_consurf) * (length(wf_consurf) - length(pivot_cols_consurf))
|
|
# expected_rows_lf
|
|
|
|
# LF data: consurf
|
|
lf_consurf = gather(wf_consurf
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(consurf_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_consurf) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", consurf_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_consurf$outcome_colname = "consurf_outcome"
|
|
lf_consurf$outcome = lf_consurf$consurf_outcome
|
|
|
|
# DROP static cols
|
|
lf_consurf = lf_consurf[!lf_consurf$param_type%in%c(static_cols_end),]
|
|
lf_consurf$param_type = factor(lf_consurf$param_type)
|
|
table(lf_consurf$param_type); colnames(lf_consurf)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_consurf']] = wf_consurf
|
|
wf_lf_dataL[['lf_consurf']] = lf_consurf
|
|
###########################################################################
|
|
#==============
|
|
# SNAP2: LF
|
|
#==============
|
|
# WF data: snap2
|
|
cols_to_select_snap2 = c(static_cols_start, c("snap2_outcome", snap2_dn), static_cols_end)
|
|
wf_snap2 = comb_df_sl[, cols_to_select_snap2]
|
|
|
|
pivot_cols_snap2 = cols_to_select_snap2[1: (length(static_cols_start) + 1)]; pivot_cols_snap2
|
|
expected_rows_lf = nrow(wf_snap2) * (length(wf_snap2) - length(pivot_cols_snap2))
|
|
expected_rows_lf
|
|
|
|
# LF data: snap2
|
|
lf_snap2 = gather(wf_snap2
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(snap2_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_snap2) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", snap2_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_snap2$outcome_colname = "snap2_outcome"
|
|
lf_snap2$outcome = lf_snap2$snap2_outcome
|
|
|
|
# DROP static cols
|
|
lf_snap2 = lf_snap2[!lf_snap2$param_type%in%c(static_cols_end),]
|
|
lf_snap2$param_type = factor(lf_snap2$param_type)
|
|
table(lf_snap2$param_type); colnames(lf_snap2)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_snap2']] = wf_snap2
|
|
wf_lf_dataL[['lf_snap2']] = lf_snap2
|
|
|
|
#==============
|
|
# Provean2: LF
|
|
#==============
|
|
# WF data: provean
|
|
cols_to_select_provean = c(static_cols_start, c("provean_outcome", provean_dn), static_cols_end)
|
|
wf_provean = comb_df_sl[, cols_to_select_provean]
|
|
|
|
pivot_cols_provean = cols_to_select_provean[1: (length(static_cols_start) + 1)]; pivot_cols_provean
|
|
expected_rows_lf = nrow(wf_provean) * (length(wf_provean) - length(pivot_cols_provean))
|
|
expected_rows_lf
|
|
|
|
# LF data: provean
|
|
lf_provean = gather(wf_provean
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(provean_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_provean) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", provean_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_provean$outcome_colname = "provean_outcome"
|
|
lf_provean$outcome = lf_provean$provean_outcome
|
|
|
|
# DROP static cols
|
|
lf_provean = lf_provean[!lf_provean$param_type%in%c(static_cols_end),]
|
|
lf_provean$param_type = factor(lf_provean$param_type)
|
|
table(lf_provean$param_type); colnames(lf_provean)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_provean']] = wf_provean
|
|
wf_lf_dataL[['lf_provean']] = lf_provean
|
|
|
|
|
|
###########################################################################
|
|
# AFFINITY cols
|
|
###########################################################################
|
|
#=========================
|
|
# mCSM-lig:
|
|
# data filtered by cut off
|
|
#=========================
|
|
#---------------------
|
|
# mCSM-lig: WF and lF
|
|
#----------------------
|
|
# WF data: mcsm_lig
|
|
cols_to_select_mcsm_lig = c(static_cols_start, c("ligand_outcome", mcsm_lig_dn), static_cols_end)
|
|
wf_mcsm_lig = comb_df_sl_lig[, cols_to_select_mcsm_lig] # filtered df
|
|
|
|
pivot_cols_mcsm_lig = cols_to_select_mcsm_lig[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_lig
|
|
expected_rows_lf = nrow(wf_mcsm_lig) * (length(wf_mcsm_lig) - length(pivot_cols_mcsm_lig))
|
|
expected_rows_lf
|
|
|
|
# LF data: mcsm_lig
|
|
lf_mcsm_lig = gather(wf_mcsm_lig
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(mcsm_lig_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_mcsm_lig) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", mcsm_lig_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for mcsm_lig")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_mcsm_lig$outcome_colname = "ligand_outcome"
|
|
lf_mcsm_lig$outcome = lf_mcsm_lig$ligand_outcome
|
|
|
|
# DROP static cols
|
|
lf_mcsm_lig = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_cols_end),]
|
|
lf_mcsm_lig$param_type = factor(lf_mcsm_lig$param_type)
|
|
table(lf_mcsm_lig$param_type); colnames(lf_mcsm_lig)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_mcsm_lig']] = wf_mcsm_lig
|
|
wf_lf_dataL[['lf_mcsm_lig']] = lf_mcsm_lig
|
|
|
|
#=========================
|
|
# mmCSM-lig2:
|
|
# data filtered by cut off
|
|
#=========================
|
|
#---------------------
|
|
# mmCSM-lig2: WF and lF
|
|
#----------------------
|
|
# WF data: mmcsm_lig2
|
|
cols_to_select_mmcsm_lig2 = c(static_cols_start, c("mmcsm_lig_outcome", mmcsm_lig_dn2), static_cols_end)
|
|
wf_mmcsm_lig2 = comb_df_sl_lig[, cols_to_select_mmcsm_lig2] # filtered df
|
|
|
|
pivot_cols_mmcsm_lig2 = cols_to_select_mmcsm_lig2[1: (length(static_cols_start) + 1)]; pivot_cols_mmcsm_lig2
|
|
expected_rows_lf = nrow(wf_mmcsm_lig2) * (length(wf_mmcsm_lig2) - length(pivot_cols_mmcsm_lig2))
|
|
expected_rows_lf
|
|
|
|
# LF data: mmcsm_lig2
|
|
lf_mmcsm_lig2 = gather(wf_mmcsm_lig2
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(mmcsm_lig_dn2):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_mmcsm_lig2) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", mmcsm_lig_dn2)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for mmcsm_lig2")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_mmcsm_lig2$outcome_colname = "mmcsm_lig_outcome"
|
|
lf_mmcsm_lig2$outcome = lf_mmcsm_lig2$mmcsm_lig_outcome
|
|
|
|
# DROP static cols
|
|
lf_mmcsm_lig2 = lf_mmcsm_lig2[!lf_mmcsm_lig2$param_type%in%c(static_cols_end),]
|
|
lf_mmcsm_lig2$param_type = factor(lf_mmcsm_lig2$param_type)
|
|
table(lf_mmcsm_lig2$param_type); colnames(lf_mmcsm_lig2)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_mmcsm_lig2']] = wf_mmcsm_lig2
|
|
wf_lf_dataL[['lf_mmcsm_lig2']] = lf_mmcsm_lig2
|
|
|
|
#=========================
|
|
# mcsm-ppi2 affinity
|
|
# data filtered by cut off
|
|
#========================
|
|
if (tolower(gene)%in%geneL_ppi2){
|
|
#-----------------
|
|
# mCSM-PPI2: WF and lF
|
|
#-----------------
|
|
# WF data: mcsm-ppi2
|
|
cols_to_select_mcsm_ppi2 = c(static_cols_start, c("mcsm_ppi2_outcome", mcsm_ppi2_dn), static_cols_end)
|
|
#wf_mcsm_ppi2 = comb_df_sl[, cols_to_select_mcsm_ppi2]
|
|
wf_mcsm_ppi2 = comb_df_sl_ppi2[, cols_to_select_mcsm_ppi2]
|
|
|
|
pivot_cols_mcsm_ppi2 = cols_to_select_mcsm_ppi2[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_ppi2
|
|
expected_rows_lf = nrow(wf_mcsm_ppi2) * (length(wf_mcsm_ppi2) - length(pivot_cols_mcsm_ppi2))
|
|
expected_rows_lf
|
|
|
|
# LF data: mcsm-ppi2
|
|
lf_mcsm_ppi2 = gather(wf_mcsm_ppi2
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(mcsm_ppi2_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_mcsm_ppi2) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", mcsm_ppi2_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_mcsm_ppi2$outcome_colname = "mcsm_ppi2_outcome"
|
|
lf_mcsm_ppi2$outcome = lf_mcsm_ppi2$mcsm_ppi2_outcome
|
|
|
|
# DROP static cols
|
|
lf_mcsm_ppi2 = lf_mcsm_ppi2[!lf_mcsm_ppi2$param_type%in%c(static_cols_end),]
|
|
lf_mcsm_ppi2$param_type = factor(lf_mcsm_ppi2$param_type)
|
|
table(lf_mcsm_ppi2$param_type); colnames(lf_mcsm_ppi2)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_mcsm_ppi2']] = wf_mcsm_ppi2
|
|
wf_lf_dataL[['lf_mcsm_ppi2']] = lf_mcsm_ppi2
|
|
|
|
}
|
|
|
|
|
|
|
|
#====================
|
|
# mcsm-NA affinity
|
|
# data filtered by cut off
|
|
#====================
|
|
if (tolower(gene)%in%geneL_na){
|
|
#---------------
|
|
# mCSM-NA: WF and lF
|
|
#-----------------
|
|
# WF data: mcsm-na
|
|
cols_to_select_mcsm_na = c(static_cols_start, c("mcsm_na_outcome", mcsm_na_dn), static_cols_end)
|
|
#wf_mcsm_na = comb_df_sl[, cols_to_select_mcsm_na]
|
|
wf_mcsm_na = comb_df_sl_na[, cols_to_select_mcsm_na]
|
|
|
|
pivot_cols_mcsm_na = cols_to_select_mcsm_na[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_na
|
|
expected_rows_lf = nrow(wf_mcsm_na) * (length(wf_mcsm_na) - length(pivot_cols_mcsm_na))
|
|
expected_rows_lf
|
|
|
|
# LF data: mcsm-na
|
|
lf_mcsm_na = gather(wf_mcsm_na
|
|
, key = param_type
|
|
, value = param_value
|
|
, all_of(mcsm_na_dn):tail(static_cols_end,1)
|
|
, factor_key = TRUE)
|
|
|
|
if (nrow(lf_mcsm_na) == expected_rows_lf){
|
|
cat("\nPASS: long format data created for ", mcsm_na_dn)
|
|
}else{
|
|
cat("\nFAIL: long format data could not be created for duet")
|
|
quit()
|
|
}
|
|
|
|
# NEW columns [outcome and outcome colname]
|
|
lf_mcsm_na$outcome_colname = "mcsm_na_outcome"
|
|
lf_mcsm_na$outcome = lf_mcsm_na$mcsm_na_outcome
|
|
|
|
# DROP static cols
|
|
lf_mcsm_na = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_cols_end),]
|
|
lf_mcsm_na$param_type = factor(lf_mcsm_na$param_type)
|
|
table(lf_mcsm_na$param_type); colnames(lf_mcsm_na)
|
|
|
|
# Assign them to the output list
|
|
wf_lf_dataL[['wf_mcsm_na']] = wf_mcsm_na
|
|
wf_lf_dataL[['lf_mcsm_na']] = lf_mcsm_na
|
|
|
|
}
|
|
|
|
return(wf_lf_dataL)
|
|
}
|
|
############################################################################
|