playing with dm_om (other)plots data and graph on gid branch
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4 changed files with 502 additions and 410 deletions
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@ -5,21 +5,18 @@
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#########################################################
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#=======================================================================
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# working dir and loading libraries
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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# getwd()
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# setwd("~/git/LSHTM_analysis/scripts/plotting")
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# getwd()
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#source("Header_TT.R")
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library(ggplot2)
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library(data.table)
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library(dplyr)
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library(tidyverse)
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source("combining_dfs_plotting.R")
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rm(merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig
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, merged_df3_comp, merged_df3_comp_lig
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, my_df_u, my_df_u_lig)
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# make cmd
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# globals
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# drug = "streptomycin"
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# gene = "gid"
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#source("get_plotting_dfs.R")
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#=======================================================================
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# MOVE TO COMBINE or singular file for deepddg
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cols_to_select = c("mutation", "mutationinformation"
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, "wild_type", "position", "mutant_type"
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@ -27,275 +24,515 @@ cols_to_select = c("mutation", "mutationinformation"
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merged_df3_short = merged_df3[, cols_to_select]
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# write merged_df3 to generate structural figure
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write.csv(merged_df3_short, "merged_df3_short.csv")
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infilename_mcsm_f_snps <- paste0("~/git/Data/", drug, "/output/", gene
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, "_mcsm_formatted_snps.csv")
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mcsm_f_snps<- read.csv(infilename_mcsm_f_snps, header = F)
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names(mcsm_f_snps) <- "mutationinformation"
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# write merged_df3 to generate structural figure on chimera
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#write.csv(merged_df3_short, "merged_df3_short.csv")
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#========================================================================
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#%%%%%%%%%%%%%%%%%%%
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# REASSIGNMENT: PS
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#%%%%%%%%%%%%%%%%%%%%
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df_ps = merged_df3
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# MOVE TO COMBINE or singular file for deepddg
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#============================
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# adding foldx scaled values
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# adding deepddg scaled values
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# scale data b/w -1 and 1
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#============================
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n = which(colnames(df_ps) == "ddg"); n
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n = which(colnames(merged_df3) == "deepddg"); n
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my_min = min(df_ps[,n]); my_min
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my_max = max(df_ps[,n]); my_max
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my_min = min(merged_df3[,n]); my_min
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my_max = max(merged_df3[,n]); my_max
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df_ps$foldx_scaled = ifelse(df_ps[,n] < 0
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, df_ps[,n]/abs(my_min)
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, df_ps[,n]/my_max)
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merged_df3$deepddg_scaled = ifelse(merged_df3[,n] < 0
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, merged_df3[,n]/abs(my_min)
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, merged_df3[,n]/my_max)
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# sanity check
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my_min = min(df_ps$foldx_scaled); my_min
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my_max = max(df_ps$foldx_scaled); my_max
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my_min = min(merged_df3$deepddg_scaled); my_min
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my_max = max(merged_df3$deepddg_scaled); my_max
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if (my_min == -1 && my_max == 1){
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cat("PASS: foldx ddg successfully scaled b/w -1 and 1"
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, "\nProceeding with assigning foldx outcome category")
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cat("PASS: DeepDDG successfully scaled b/w -1 and 1"
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#, "\nProceeding with assigning deep outcome category")
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, "\n")
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}else{
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cat("FAIL: could not scale foldx ddg values"
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cat("FAIL: could not scale DeepDDG ddg values"
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, "Aborting!")
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}
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#================================
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# adding foldx outcome category
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# ddg<0 = "Stabilising" (-ve)
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#=================================
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#========================================================================
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# cols to select
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c1 = table(df_ps$ddg < 0)
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df_ps$foldx_outcome = ifelse(df_ps$ddg < 0, "Stabilising", "Destabilising")
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c2 = table(df_ps$ddg < 0)
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cols_mcsm_df <- merged_df3[, c("mutationinformation", "mutation"
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, "mutation_info", "position"
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, LigDist_colname
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, "duet_stability_change", "duet_scaled", "duet_outcome"
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, "ligand_affinity_change", "affinity_scaled", "ligand_outcome"
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, "ddg_foldx", "foldx_scaled", "foldx_outcome"
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, "deepddg", "deepddg_scaled", "deepddg_outcome"
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, "asa", "rsa"
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, "rd_values", "kd_values"
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, "log10_or_mychisq", "neglog_pval_fisher", "af")]
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if ( all(c1 == c2) ){
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cat("PASS: foldx outcome successfully created")
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}else{
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cat("FAIL: foldx outcome could not be created. Aborting!")
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exit()
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cols_mcsm_na_df <- mcsm_na_df[, c("mutationinformation"
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, "mcsm_na_affinity", "mcsm_na_scaled"
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, "mcsm_na_outcome")]
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# entire dynamut_df
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cols_dynamut2_df <- dynamut2_df[, c("mutationinformation"
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, "ddg_dynamut2", "ddg_dynamut2_scaled"
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, "ddg_dynamut2_outcome")]
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n_comb_cols = length(cols_mcsm_df) + length(cols_mcsm_na_df) +
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length(dynamut_df) + length(cols_dynamut2_df); n_comb_cols
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i1<- intersect(names(cols_mcsm_df), names(cols_mcsm_na_df))
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i2<- intersect(names(dynamut_df), names(cols_dynamut2_df))
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merging_cols <- intersect(i1, i2)
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cat("\nmerging_cols:", merging_cols)
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if (merging_cols == "mutationinformation") {
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cat("\nStage 1: Found common col between dfs, checking values in it...")
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c1 <- all(mcsm_f_snps[[merging_cols]]%in%cols_mcsm_df[[merging_cols]])
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c2 <- all(mcsm_f_snps[[merging_cols]]%in%cols_mcsm_na_df[[merging_cols]])
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c3 <- all(mcsm_f_snps[[merging_cols]]%in%dynamut_df[[merging_cols]])
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c4 <- all(mcsm_f_snps[[merging_cols]]%in%cols_dynamut2_df[[merging_cols]])
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cols_check <- c(c1, c2, c3, c4)
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expected_cols = n_comb_cols - ( length(cols_check) - 1)
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if (all(cols_check)){
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cat("\nStage 2:Proceeding with merging dfs:\n")
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comb_df <- Reduce(inner_join, list(cols_mcsm_df
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, cols_mcsm_na_df
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, dynamut_df
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, cols_dynamut2_df))
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comb_df_s = arrange(comb_df, position)
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# if ( nrow(comb_df_s) == nrow(mcsm_f_snps) && ncol(comb_df_s) == expected_cols) {
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# cat("\Stage3, PASS: dfs merged sucessfully"
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# , "\nnrow of merged_df: ", nrow(comb_df_s)
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# , "\nncol of merged_df:", ncol(comb_df_s))
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# }
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}
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}
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names(comb_df_s)
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#=======================================================================
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# name tidying
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df_ps$mutation_info = as.factor(df_ps$mutation_info)
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df_ps$duet_outcome = as.factor(df_ps$duet_outcome)
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df_ps$foldx_outcome = as.factor(df_ps$foldx_outcome)
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df_ps$ligand_outcome = as.factor(df_ps$ligand_outcome)
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fact_cols = colnames(comb_df_s)[grepl( "_outcome|_info", colnames(comb_df_s) )]
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fact_cols
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lapply(comb_df_s[, fact_cols], class)
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comb_df_s[,fact_cols] <- lapply(comb_df_s[,cols],as.factor)
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# check
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table(df_ps$mutation_info)
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if (any(lapply(comb_df_s[, fact_cols], class) == "character")){
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cat("\nChanging cols to factor")
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comb_df_s[, fact_cols] <- lapply(comb_df_s[, fact_cols],as.factor)
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if (all(lapply(comb_df_s[, fact_cols], class) == "factor")){
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cat("\nSuccessful: cols changed to factor")
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}
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}
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lapply(comb_df_s[, fact_cols], class)
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#=======================================================================
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table(comb_df_s$mutation_info)
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# further checks to make sure dr and other muts are indeed unique
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dr_muts = df_ps[df_ps$mutation_info == dr_muts_col,]
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dr_muts = comb_df_s[comb_df_s$mutation_info == dr_muts_col,]
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dr_muts_names = unique(dr_muts$mutation)
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other_muts = df_ps[df_ps$mutation_info == other_muts_col,]
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other_muts = comb_df_s[comb_df_s$mutation_info == other_muts_col,]
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other_muts_names = unique(other_muts$mutation)
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if ( table(dr_muts_names%in%other_muts_names)[[1]] == length(dr_muts_names) &&
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table(other_muts_names%in%dr_muts_names)[[1]] == length(other_muts_names) ){
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cat("PASS: dr and other muts are indeed unique")
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}else{
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cat("FAIL: dr adn others muts are NOT unique!")
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cat("FAIL: dr and others muts are NOT unique!")
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quit()
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}
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# pretty display names i.e. labels to reduce major code duplication later
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foo_cnames = data.frame(colnames(comb_df_s))
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names(foo_cnames) <- "old_name"
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#%%%%%%%%%%%%%%%%%%%
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# REASSIGNMENT: LIG
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#%%%%%%%%%%%%%%%%%%%%
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stability_suffix <- paste0(delta_symbol, delta_symbol, "G")
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flexibility_suffix <- paste0(delta_symbol, delta_symbol, "S")
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df_lig = merged_df3_lig
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lig_dn = paste0("Ligand distance (", angstroms_symbol, ")"); lig_dn
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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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mcsm_na_dn = paste0("mCSM-NA affinity ", stability_suffix); mcsm_na_dn
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dynamut_dn = paste0("Dynamut ", stability_suffix); dynamut_dn
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dynamut2_dn = paste0("Dynamut2 " , stability_suffix); dynamut2_dn
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encom_ddg_dn = paste0("EnCOM " , stability_suffix); encom_ddg_dn
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encom_dds_dn = paste0("EnCOM " , flexibility_suffix ); encom_dds_dn
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sdm_dn = paste0("SDM " , stability_suffix); sdm_dn
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mcsm_dn = paste0("mCSM " , stability_suffix ); mcsm_dn
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# name tidying
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df_lig$mutation_info = as.factor(df_lig$mutation_info)
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df_lig$duet_outcome = as.factor(df_lig$duet_outcome)
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#df_lig$ligand_outcome = as.factor(df_lig$ligand_outcome)
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# check
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table(df_lig$mutation_info)
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#========================================================================
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#===========
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# Data: ps
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#===========
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# keep similar dtypes cols together
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cols_to_select_ps = c("mutationinformation", "mutation", "position", "mutation_info"
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, "duet_outcome"
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# Change colnames of some columns using datatable
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comb_df_sl = comb_df_s
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names(comb_df_sl)
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setnames(comb_df_sl
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, old = c("asa", "rsa", "rd_values", "kd_values"
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, "log10_or_mychisq", "neglog_pval_fisher", "af"
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, LigDist_colname
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, "duet_scaled"
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, "ligand_distance"
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, "asa"
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, "rsa"
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, "rd_values"
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, "kd_values")
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, "foldx_scaled"
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, "deepddg_scaled"
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, "mcsm_na_scaled"
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, "ddg_dynamut_scaled"
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, "ddg_dynamut2_scaled"
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, "ddg_encom_scaled"
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, "dds_encom_scaled"
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, "ddg_sdm"
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, "ddg_mcsm")
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, new = c("ASA", "RSA", "RD", "KD"
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, "Log10 (OR)", "-Log (P)", "MAF"
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, lig_dn
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, duet_dn
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, foldx_dn
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, deepddg_dn
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, mcsm_na_dn
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, dynamut_dn
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, dynamut2_dn
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, encom_ddg_dn
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, encom_dds_dn
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, sdm_dn
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, mcsm_dn)
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)
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df_wf_ps = df_ps[, cols_to_select_ps]
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foo_cnames <- cbind(foo_cnames, colnames(comb_df_sl))
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pivot_cols_ps = cols_to_select_ps[1:5]; pivot_cols_ps
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# some more pretty labels
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table(comb_df_sl$mutation_info)
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expected_rows_lf_ps = nrow(df_wf_ps) * (length(df_wf_ps) - length(pivot_cols_ps))
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expected_rows_lf_ps
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levels(comb_df_sl$mutation_info)[levels(comb_df_sl$mutation_info)==dr_muts_col] <- "DM"
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levels(comb_df_sl$mutation_info)[levels(comb_df_sl$mutation_info)==other_muts_col] <- "OM"
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table(comb_df_sl$mutation_info)
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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("mutationinformation"
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, "position"
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, "mutation"
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, "mutation_info")
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static_cols_end = c(lig_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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# ordering is important!
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#########################################################################
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#==============
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# DUET: LF
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#==============
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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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df_lf_ps = gather(df_wf_ps, param_type, param_value, duet_scaled:kd_values, factor_key=TRUE)
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lf_duet = 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(df_lf_ps) == expected_rows_lf_ps){
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cat("PASS: long format data created for duet")
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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("FAIL: long format data could not be created for duet")
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exit()
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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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str(df_wf_ps)
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str(df_lf_ps)
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# assign pretty labels: param_type
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levels(df_lf_ps$param_type); table(df_lf_ps$param_type)
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ligand_dist_colname = paste0("Distance to ligand (", angstroms_symbol, ")")
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ligand_dist_colname
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duet_stability_name = paste0(delta_symbol, delta_symbol, "G")
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duet_stability_name
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#levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="duet_scaled"] <- "Stability"
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="duet_scaled"] <- duet_stability_name
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#levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="ligand_distance"] <- "Ligand Distance"
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="ligand_distance"] <- ligand_dist_colname
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="asa"] <- "ASA"
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="rsa"] <- "RSA"
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="rd_values"] <- "RD"
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levels(df_lf_ps$param_type)[levels(df_lf_ps$param_type)=="kd_values"] <- "KD"
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# check
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levels(df_lf_ps$param_type); table(df_lf_ps$param_type)
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# assign pretty labels: mutation_info
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levels(df_lf_ps$mutation_info); table(df_lf_ps$mutation_info)
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sum(table(df_lf_ps$mutation_info)) == nrow(df_lf_ps)
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levels(df_lf_ps$mutation_info)[levels(df_lf_ps$mutation_info)==dr_muts_col] <- "DM"
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levels(df_lf_ps$mutation_info)[levels(df_lf_ps$mutation_info)==other_muts_col] <- "OM"
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# check
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levels(df_lf_ps$mutation_info); table(df_lf_ps$mutation_info)
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############################################################################
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#==============
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# FoldX: LF
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#==============
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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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#===========
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# LF data: LIG
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#===========
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# keep similar dtypes cols together
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cols_to_select_lig = c("mutationinformation", "mutation", "position", "mutation_info"
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, "ligand_outcome"
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, "affinity_scaled"
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#, "ligand_distance"
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, "asa"
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, "rsa"
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, "rd_values"
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, "kd_values")
|
||||
pivot_cols_foldx = cols_to_select_foldx[1: (length(static_cols_start) + 1)]; pivot_cols_foldx
|
||||
|
||||
df_wf_lig = df_lig[, cols_to_select_lig]
|
||||
expected_rows_lf = nrow(wf_foldx) * (length(wf_foldx) - length(pivot_cols_foldx))
|
||||
expected_rows_lf
|
||||
|
||||
pivot_cols_lig = cols_to_select_lig[1:5]; pivot_cols_lig
|
||||
# LF data: duet
|
||||
print("TESTXXXXXXXXXXXXXXXXXXXXX---------------------->>>>")
|
||||
lf_foldx <<- gather(wf_foldx
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(foldx_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
expected_rows_lf_lig = nrow(df_wf_lig) * (length(df_wf_lig) - length(pivot_cols_lig))
|
||||
expected_rows_lf_lig
|
||||
|
||||
# LF data: foldx
|
||||
df_lf_lig = gather(df_wf_lig, param_type, param_value, affinity_scaled:kd_values, factor_key=TRUE)
|
||||
|
||||
if (nrow(df_lf_lig) == expected_rows_lf_lig){
|
||||
cat("PASS: long format data created for foldx")
|
||||
if (nrow(lf_foldx) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", foldx_dn)
|
||||
}else{
|
||||
cat("FAIL: long format data could not be created for foldx")
|
||||
exit()
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
|
||||
# assign pretty labels: param_type
|
||||
levels(df_lf_lig$param_type); table(df_lf_lig$param_type)
|
||||
|
||||
levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="affinity_scaled"] <- "Ligand Affinity"
|
||||
#levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="ligand_distance"] <- "Ligand Distance"
|
||||
levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="asa"] <- "ASA"
|
||||
levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="rsa"] <- "RSA"
|
||||
levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="rd_values"] <- "RD"
|
||||
levels(df_lf_lig$param_type)[levels(df_lf_lig$param_type)=="kd_values"] <- "KD"
|
||||
#check
|
||||
levels(df_lf_lig$param_type); table(df_lf_lig$param_type)
|
||||
|
||||
# assign pretty labels: mutation_info
|
||||
levels(df_lf_lig$mutation_info); table(df_lf_lig$mutation_info)
|
||||
sum(table(df_lf_lig$mutation_info)) == nrow(df_lf_lig)
|
||||
|
||||
levels(df_lf_lig$mutation_info)[levels(df_lf_lig$mutation_info)==dr_muts_col] <- "DM"
|
||||
levels(df_lf_lig$mutation_info)[levels(df_lf_lig$mutation_info)==other_muts_col] <- "OM"
|
||||
# check
|
||||
levels(df_lf_lig$mutation_info); table(df_lf_lig$mutation_info)
|
||||
|
||||
#############################################################################
|
||||
#===========
|
||||
# Data: foldx
|
||||
#===========
|
||||
# keep similar dtypes cols together
|
||||
cols_to_select_foldx = c("mutationinformation", "mutation", "position", "mutation_info"
|
||||
, "foldx_outcome"
|
||||
|
||||
, "foldx_scaled")
|
||||
#, "ligand_distance"
|
||||
#, "asa"
|
||||
#, "rsa"
|
||||
#, "rd_values"
|
||||
#, "kd_values")
|
||||
|
||||
|
||||
df_wf_foldx = df_ps[, cols_to_select_foldx]
|
||||
|
||||
pivot_cols_foldx = cols_to_select_foldx[1:5]; pivot_cols_foldx
|
||||
|
||||
expected_rows_lf_foldx = nrow(df_wf_foldx) * (length(df_wf_foldx) - length(pivot_cols_foldx))
|
||||
expected_rows_lf_foldx
|
||||
|
||||
# LF data: foldx
|
||||
df_lf_foldx = gather(df_wf_foldx, param_type, param_value, foldx_scaled, factor_key=TRUE)
|
||||
|
||||
if (nrow(df_lf_foldx) == expected_rows_lf_foldx){
|
||||
cat("PASS: long format data created for foldx")
|
||||
}else{
|
||||
cat("FAIL: long format data could not be created for foldx")
|
||||
exit()
|
||||
}
|
||||
|
||||
foldx_stability_name = paste0(delta_symbol, delta_symbol, "G")
|
||||
foldx_stability_name
|
||||
|
||||
# assign pretty labels: param type
|
||||
levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
|
||||
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="foldx_scaled"] <- "Stability"
|
||||
levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="foldx_scaled"] <- foldx_stability_name
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="ligand_distance"] <- "Ligand Distance"
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="asa"] <- "ASA"
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rsa"] <- "RSA"
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="rd_values"] <- "RD"
|
||||
#levels(df_lf_foldx$param_type)[levels(df_lf_foldx$param_type)=="kd_values"] <- "KD"
|
||||
# check
|
||||
levels(df_lf_foldx$param_type); table(df_lf_foldx$param_type)
|
||||
|
||||
# assign pretty labels: mutation_info
|
||||
levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
|
||||
sum(table(df_lf_foldx$mutation_info)) == nrow(df_lf_foldx)
|
||||
|
||||
levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==dr_muts_col] <- "DM"
|
||||
levels(df_lf_foldx$mutation_info)[levels(df_lf_foldx$mutation_info)==other_muts_col] <- "OM"
|
||||
# check
|
||||
levels(df_lf_foldx$mutation_info); table(df_lf_foldx$mutation_info)
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# Deepddg: LF
|
||||
#==============
|
||||
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]
|
||||
|
||||
# clear excess variables
|
||||
rm(cols_to_select_ps, cols_to_select_foldx, cols_to_select_lig
|
||||
, pivot_cols_ps, pivot_cols_foldx, pivot_cols_lig
|
||||
, expected_rows_lf_ps, expected_rows_lf_foldx, expected_rows_lf_lig
|
||||
, my_max, my_min, na_count, na_count_df2, na_count_df3, dup_muts_nu
|
||||
, c1, c2, n)
|
||||
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: duet
|
||||
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()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# mCSM-NA: LF
|
||||
#==============
|
||||
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]
|
||||
|
||||
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: duet
|
||||
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()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# Dynamut: LF
|
||||
#==============
|
||||
cols_to_select_dynamut = c(static_cols_start, c("ddg_dynamut_outcome", dynamut_dn), static_cols_end)
|
||||
wf_dynamut = comb_df_sl[, cols_to_select_dynamut]
|
||||
|
||||
pivot_cols_dynamut = cols_to_select_dynamut[1: (length(static_cols_start) + 1)]; pivot_cols_dynamut
|
||||
|
||||
expected_rows_lf = nrow(wf_dynamut) * (length(wf_dynamut) - length(pivot_cols_dynamut))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: duet
|
||||
lf_dynamut = gather(wf_dynamut
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(dynamut_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_dynamut) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", dynamut_dn)
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# Dynamut2: LF
|
||||
#==============
|
||||
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: duet
|
||||
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()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# EnCOM ddg: LF
|
||||
#==============
|
||||
cols_to_select_encomddg = c(static_cols_start, c("ddg_encom_outcome", encom_ddg_dn), static_cols_end)
|
||||
wf_encomddg = comb_df_sl[, cols_to_select_encomddg]
|
||||
|
||||
pivot_cols_encomddg = cols_to_select_encomddg[1: (length(static_cols_start) + 1)]; pivot_cols_encomddg
|
||||
|
||||
expected_rows_lf = nrow(wf_encomddg ) * (length(wf_encomddg ) - length(pivot_cols_encomddg))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: encomddg
|
||||
lf_encomddg = gather(wf_encomddg
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(encom_ddg_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_encomddg) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for ", encom_ddg_dn)
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
############################################################################
|
||||
#==============
|
||||
# EnCOM dds: LF
|
||||
#==============
|
||||
cols_to_select_encomdds = c(static_cols_start, c("dds_encom_outcome", encom_dds_dn), static_cols_end)
|
||||
wf_encomdds = comb_df_sl[, cols_to_select_encomdds]
|
||||
|
||||
pivot_cols_encomdds = cols_to_select_encomdds[1: (length(static_cols_start) + 1)]; pivot_cols_encomdds
|
||||
|
||||
expected_rows_lf = nrow(wf_encomdds) * (length(wf_encomdds) - length(pivot_cols_encomdds))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: encomddg
|
||||
lf_encomdds = gather(wf_encomdds
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(encom_dds_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_encomdds) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for", encom_dds_dn)
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# SDM: LF
|
||||
#==============
|
||||
cols_to_select_sdm = c(static_cols_start, c("ddg_sdm_outcome", sdm_dn), static_cols_end)
|
||||
wf_sdm = comb_df_sl[, cols_to_select_sdm]
|
||||
|
||||
pivot_cols_sdm = cols_to_select_sdm[1: (length(static_cols_start) + 1)]; pivot_cols_sdm
|
||||
|
||||
expected_rows_lf = nrow(wf_sdm) * (length(wf_sdm) - length(pivot_cols_sdm))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: encomddg
|
||||
lf_sdm = gather(wf_sdm
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(sdm_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_sdm) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for", sdm_dn)
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
|
||||
############################################################################
|
||||
#==============
|
||||
# mCSM: LF
|
||||
#==============
|
||||
cols_to_select_mcsm = c(static_cols_start, c("ddg_mcsm_outcome", mcsm_dn), static_cols_end)
|
||||
wf_mcsm = comb_df_sl[, cols_to_select_mcsm]
|
||||
|
||||
pivot_cols_mcsm = cols_to_select_mcsm[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm
|
||||
|
||||
expected_rows_lf = nrow(wf_mcsm) * (length(wf_mcsm) - length(pivot_cols_mcsm))
|
||||
expected_rows_lf
|
||||
|
||||
# LF data: encomddg
|
||||
lf_mcsm = gather(wf_mcsm
|
||||
, key = param_type
|
||||
, value = param_value
|
||||
, all_of(mcsm_dn):tail(static_cols_end,1)
|
||||
, factor_key = TRUE)
|
||||
|
||||
if (nrow(lf_mcsm) == expected_rows_lf){
|
||||
cat("\nPASS: long format data created for", mcsm_dn)
|
||||
}else{
|
||||
cat("\nFAIL: long format data could not be created for duet")
|
||||
quit()
|
||||
}
|
||||
############################################################################
|
||||
# # clear excess variables
|
||||
# rm(all_plot_dfs
|
||||
# , cols_dynamut2_df
|
||||
# , cols_mcsm_df
|
||||
# , cols_mcsm_na_df
|
||||
# , comb_df
|
||||
# , corr_data_ps
|
||||
# , corr_ps_df3
|
||||
# , df_lf_ps
|
||||
# , foo
|
||||
# , foo_cnames
|
||||
# , gene_metadata
|
||||
# , logo_data
|
||||
# , logo_data_or_mult
|
||||
# , logo_data_plot
|
||||
# , logo_data_plot_logor
|
||||
# , logo_data_plot_or
|
||||
# , my_data_snp
|
||||
# , my_df
|
||||
# , my_df_u
|
||||
# , ols_mcsm_df
|
||||
# , other_muts
|
||||
# , pd_df
|
||||
# , subcols_df_ps
|
||||
# , tab_mt
|
||||
# , wide_df_logor
|
||||
# , wide_df_logor_m
|
||||
# , wide_df_or
|
||||
# , wide_df_or_mult
|
||||
# , wt)
|
||||
#
|
||||
#
|
||||
# rm(c3, c4, check1
|
||||
# , cols_check
|
||||
# , cols_to_select
|
||||
# , cols_to_select_deepddg
|
||||
# , cols_to_select_duet
|
||||
# , cols_to_select_dynamut
|
||||
# , cols_to_select_dynamut2
|
||||
# , cols_to_select_encomddg
|
||||
# , cols_to_select_encomdds
|
||||
# , cols_to_select_mcsm
|
||||
# , cols_to_select_mcsm_na
|
||||
# , cols_to_select_sdm)
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue