separating mcsm_mean_stability_ensemble from combined script
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06e5363112
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2 changed files with 99 additions and 180 deletions
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@ -10,7 +10,7 @@
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# rendering on chimera
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# read mcsm mean stability value files
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# extract the respecitve mean values and assign to the
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# extract the respective mean values and assign to the
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# b-factor column within their respective pdbs
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# generate some distribution plots for inspection
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@ -52,7 +52,8 @@ cat(gene_match)
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datadir = paste0("~/git/Data")
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indir = paste0(datadir, "/", drug, "/input")
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outdir = paste0("~/git/Data", "/", drug, "/output")
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outdir_plots = paste0("~/git/Data", "/", drug, "/output/plots")
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#outdir_plots = paste0("~/git/Data", "/", drug, "/output/plots")
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outdir_plots = paste0("~/git/Writing/thesis/images/results/", tolower(gene))
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#======
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# input
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@ -61,14 +62,19 @@ in_filename_pdb = paste0(tolower(gene), "_complex.pdb")
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infile_pdb = paste0(indir, "/", in_filename_pdb)
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cat(paste0("Input file:", infile_pdb) )
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in_filename_mean_stability = paste0(tolower(gene), "_mean_stability.csv")
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infile_mean_stability = paste0(outdir, "/", in_filename_mean_stability)
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#in_filename_mean_stability = paste0(tolower(gene), "_mean_stability.csv")
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#infile_mean_stability = paste0(outdir, "/", in_filename_mean_stability)
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in_filename_mean_stability = paste0(tolower(gene), "_mean_ens_stab_aff.csv")
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infile_mean_stability = paste0(outdir_plots, "/", in_filename_mean_stability)
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cat(paste0("Input file:", infile_mean_stability) )
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#=======
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# output
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#=======
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out_filename_duet_mspdb = paste0(tolower(gene), "_complex_bduet_ms.pdb")
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#out_filename_duet_mspdb = paste0(tolower(gene), "_complex_bduet_ms.pdb")
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out_filename_duet_mspdb = paste0(tolower(gene), "_complex_b_stab_ms.pdb")
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outfile_duet_mspdb = paste0(outdir_plots, "/", out_filename_duet_mspdb)
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print(paste0("Output file:", outfile_duet_mspdb))
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@ -77,6 +83,8 @@ outfile_lig_mspdb = paste0(outdir_plots, "/", out_filename_lig_mspdb)
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print(paste0("Output file:", outfile_lig_mspdb))
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#%%===============================================================
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#NOTE: duet here refers to the ensemble stability values
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###########################
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# Read file: average stability values
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# or mcsm_normalised file
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@ -133,17 +141,17 @@ par(oma = c(3,2,3,0)
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#, mfrow = c(3,2)
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, mfrow = c(3,4))
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#************
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#=============
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# Row 1 plots: original B-factors
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# duet and affinity
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#************
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#=============
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hist(df_duet$b
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, xlab = ""
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, main = "Bfactor duet")
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, main = "Bfactor stability")
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plot(density(df_duet$b)
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, xlab = ""
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, main = "Bfactor duet")
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, main = "Bfactor stability")
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hist(df_lig$b
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@ -154,32 +162,36 @@ plot(density(df_lig$b)
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, xlab = ""
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, main = "Bfactor affinity")
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#************
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#=============
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# Row 2 plots: original mean stability values
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# duet and affinity
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#************
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hist(my_df$averaged_duet
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#=============
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#hist(my_df$averaged_duet
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hist(my_df$avg_ens_stability_scaled
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, xlab = ""
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, main = "mean duet values")
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, main = "mean stability values")
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plot(density(my_df$averaged_duet)
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#plot(density(my_df$averaged_duet)
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plot(density(my_df$avg_ens_stability_scaled)
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, xlab = ""
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, main = "mean duet values")
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, main = "mean stability values")
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hist(my_df$averaged_affinity
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#hist(my_df$averaged_affinity
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hist(my_df$avg_ens_affinity_scaled
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, xlab = ""
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, main = "mean affinity values")
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plot(density(my_df$averaged_affinity)
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#plot(density(my_df$averaged_affinity)
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plot(density(my_df$avg_ens_affinity_scaled)
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, xlab = ""
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, main = "mean affinity values")
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#************
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#==============
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# Row 3 plots: replaced B-factors with mean stability values
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# After actual replacement in the b factor column
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#*************
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#=========================================================
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#===============
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################################################################
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#=========
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# step 0_P1: DONT RUN once you have double checked the matched output
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#=========
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@ -192,49 +204,54 @@ plot(density(my_df$averaged_affinity)
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#=========
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# Be brave and replace in place now (don"t run sanity check)
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# this makes all the B-factor values in the non-matched positions as NA
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df_duet$b = my_df$averaged_duet_scaled[match(df_duet$resno, my_df$position)]
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df_lig$b = my_df$averaged_affinity_scaled[match(df_lig$resno, my_df$position)]
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#df_duet$b = my_df$averaged_duet_scaled[match(df_duet$resno, my_df$position)]
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#df_lig$b = my_df$averaged_affinity_scaled[match(df_lig$resno, my_df$position)]
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df_duet$b = my_df$avg_ens_stability_scaled[match(df_duet$resno, my_df$position)]
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df_lig$b = my_df$avg_ens_affinity_scaled[match(df_lig$resno, my_df$position)]
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#=========
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# step 2_P1
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#=========
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# count NA in Bfactor
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b_na_duet = sum(is.na(df_duet$b)) ; b_na_duet
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b_na_lig = sum(is.na(df_lig$b)) ; b_na_lig
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b_na_lig = sum(is.na(df_lig$b)) ; b_na_lig
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# count number of 0"s in Bactor
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sum(df_duet$b == 0)
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sum(df_lig$b == 0)
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sum(df_lig$b == 0)
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# replace all NA in b factor with 0
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df_duet$b[is.na(df_duet$b)] = 0
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df_lig$b[is.na(df_lig$b)] = 0
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na_rep = 2
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df_duet$b[is.na(df_duet$b)] = na_rep
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df_lig$b[is.na(df_lig$b)] = na_rep
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# sanity check: should be 0 and True
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# duet and lig
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if ( (sum(df_duet$b == 0) == b_na_duet) && (sum(df_lig$b == 0) == b_na_lig) ) {
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print ("PASS: NA's replaced with 0s successfully in df_duet and df_lig")
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} else {
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print("FAIL: NA replacement in df_duet NOT successful")
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quit()
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}
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# # sanity check: should be 0 and True
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# # duet and lig
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# if ( (sum(df_duet$b == na_rep) == b_na_duet) && (sum(df_lig$b == na_rep) == b_na_lig) ) {
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# print ("PASS: NA's replaced with 0s successfully in df_duet and df_lig")
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# } else {
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# print("FAIL: NA replacement in df_duet NOT successful")
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# quit()
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# }
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#
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# max(df_duet$b); min(df_duet$b)
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#
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# # sanity checks: should be True
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# if( (max(df_duet$b) == max(my_df$avg_ens_stability_scaled)) & (min(df_duet$b) == min(my_df$avg_ens_stability_scaled)) ){
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# print("PASS: B-factors replaced correctly in df_duet")
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# } else {
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# print ("FAIL: To replace B-factors in df_duet")
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# quit()
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# }
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max(df_duet$b); min(df_duet$b)
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# sanity checks: should be True
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if( (max(df_duet$b) == max(my_df$averaged_duet_scaled)) & (min(df_duet$b) == min(my_df$averaged_duet_scaled)) ){
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print("PASS: B-factors replaced correctly in df_duet")
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} else {
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print ("FAIL: To replace B-factors in df_duet")
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quit()
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}
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if( (max(df_lig$b) == max(my_df$averaged_affinity_scaled)) & (min(df_lig$b) == min(my_df$averaged_affinity_scaled)) ){
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print("PASS: B-factors replaced correctly in df_lig")
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} else {
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print ("FAIL: To replace B-factors in df_lig")
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quit()
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}
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# if( (max(df_lig$b) == max(my_df$avg_ens_affinity_scaled)) & (min(df_lig$b) == min(my_df$avg_ens_affinity_scaled)) ){
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# print("PASS: B-factors replaced correctly in df_lig")
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# } else {
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# print ("FAIL: To replace B-factors in df_lig")
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# quit()
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# }
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#=========
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# step 3_P1
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@ -255,6 +272,8 @@ if ( (dim(df_duet)[1] == dim(d2_duet)[1]) & (dim(df_lig)[1] == dim(d2_lig)[1]) &
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# assign it back to the pdb file
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my_pdb_duet[['atom']] = df_duet
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max(df_duet$b); min(df_duet$b)
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table(df_duet$b)
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sum(is.na(df_duet$b))
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my_pdb_lig[['atom']] = df_lig
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max(df_lig$b); min(df_lig$b)
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@ -268,9 +287,9 @@ write.pdb(my_pdb_duet, outfile_duet_mspdb)
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cat(paste0("output file ligand mean stability pdb:", outfile_lig_mspdb))
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write.pdb(my_pdb_lig, outfile_lig_mspdb)
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#********************************
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#============================
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# Add the 3rd histogram and density plots for comparisons
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#********************************
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#============================
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# Plots continued...
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# Row 3 plots: hist and density of replaced B-factors with stability values
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hist(df_duet$b
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@ -296,16 +315,17 @@ mtext(text = "Frequency"
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, line = 0
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, outer = TRUE)
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mtext(text = "Stability Distribution"
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mtext(text = paste0(tolower(gene), ": Stability Distribution")
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, side = 3
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, line = 0
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, outer = TRUE)
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#********************************
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#============================================
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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# NOTE: This replaced B-factor distribution has the same
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# x-axis as the PredAff normalised values, but the distribution
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# is affected since 0 is overinflated. This is because all the positions
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# is affected since 0 is overinflated/or hs an additional blip because
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# of the positions not associated with resistance. This is because all the positions
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# where there are no SNPs have been assigned 0???
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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