163 lines
5.7 KiB
R
Executable file
163 lines
5.7 KiB
R
Executable file
getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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#########################################################
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# TASK:
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#########################################################
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#source("~/git/LSHTM_analysis/scripts/Header_TT.R")
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#require(data.table)
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#require(dplyr)
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source("plotting_data.R")
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# should return
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#my_df
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#my_df_u
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#dup_muts
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# cmd parse arguments
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#require('getopt', quietly = TRUE)
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#========================================================
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#========================================================
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# Read file: call script for combining df for PS
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#source("../combining_two_df.R")
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#========================================================
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# plotting_data.R imports all the dir names, etc
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#=======
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# output
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#=======
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out_filename_mean_stability = paste0(tolower(gene), "_mean_stability.csv")
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outfile_mean_stability = paste0(outdir, "/", out_filename_mean_stability)
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print(paste0("Output file:", outfile_mean_stability))
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#%%===============================================================
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#================
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# Data for plots
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#================
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# REASSIGNMENT as necessary
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df = my_df_u
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rm(my_df)
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###########################
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# Data for bfactor figure
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# PS (duet) average
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# Ligand affinity average
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###########################
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head(df$position); head(df$mutationinformation)
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head(df$duet_stability_change)
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# order data frame
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#df = df[order(df$position),] #already done
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#head(df$position); head(df$mutationinformation)
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#head(df$duet_stability_change)
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#***********
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# PS(duet): average by position and then scale b/w -1 and 1
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# column to average: duet_stability_change (NOT scaled!)
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#***********
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mean_duet_by_position <- df %>%
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group_by(position) %>%
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summarize(averaged_duet = mean(duet_stability_change))
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# scale b/w -1 and 1
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duet_min = min(mean_duet_by_position['averaged_duet'])
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duet_max = max(mean_duet_by_position['averaged_duet'])
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# scale the averaged_duet values
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mean_duet_by_position['averaged_duet_scaled'] = lapply(mean_duet_by_position['averaged_duet']
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, function(x) ifelse(x < 0, x/abs(duet_min), x/duet_max))
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cat(paste0('Average duet scores:\n', head(mean_duet_by_position['averaged_duet'])
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, '\n---------------------------------------------------------------'
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, '\nScaled duet scores:\n', head(mean_duet_by_position['averaged_duet_scaled'])))
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# sanity checks
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l_bound_duet = min(mean_duet_by_position['averaged_duet_scaled'])
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u_bound_duet = max(mean_duet_by_position['averaged_duet_scaled'])
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if ( (l_bound_duet == -1) && (u_bound_duet == 1) ){
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cat(paste0("PASS: duet scores averaged by position and then scaled"
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, "\nmin averaged duet: ", l_bound_duet
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, "\nmax averaged duet: ", u_bound_duet))
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}else{
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cat(paste0("FAIL: avergaed duet scores could not be scaled b/w -1 and 1"
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, "\nmin averaged duet: ", l_bound_duet
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, "\nmax averaged duet: ", u_bound_duet))
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quit()
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}
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#***********
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# Lig: average by position and then scale b/w -1 and 1
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# column: ligand_affinity_change (NOT scaled!)
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#***********
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mean_affinity_by_position <- df %>%
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group_by(position) %>%
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summarize(averaged_affinity = mean(ligand_affinity_change))
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# scale b/w -1 and 1
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affinity_min = min(mean_affinity_by_position['averaged_affinity'])
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affinity_max = max(mean_affinity_by_position['averaged_affinity'])
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# scale the averaged_affinity values
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mean_affinity_by_position['averaged_affinity_scaled'] = lapply(mean_affinity_by_position['averaged_affinity']
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, function(x) ifelse(x < 0, x/abs(affinity_min), x/affinity_max))
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cat(paste0('Average affinity scores:\n', head(mean_affinity_by_position['averaged_affinity'])
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, '\n---------------------------------------------------------------'
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, '\nScaled affinity scores:\n', head(mean_affinity_by_position['averaged_affinity_scaled'])))
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# sanity checks
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l_bound_affinity = min(mean_affinity_by_position['averaged_affinity_scaled'])
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u_bound_affinity = max(mean_affinity_by_position['averaged_affinity_scaled'])
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if ( (l_bound_affinity == -1) && (u_bound_affinity == 1) ){
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cat(paste0("PASS: affinity scores averaged by position and then scaled"
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, "\nmin averaged affintiy: ", l_bound_affinity
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, "\nmax averaged affintiy: ", u_bound_affinity))
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}else{
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cat(paste0("FAIL: avergaed affinity scores could not be scaled b/w -1 and 1"
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, "\nmin averaged affintiy: ", l_bound_affinity
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, "\nmax averaged affintiy: ", u_bound_affinity))
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quit()
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}
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#***********
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# merge: mean_duet_by_position and mean_affinity_by_position
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#***********
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common_cols = intersect(colnames(mean_duet_by_position), colnames(mean_affinity_by_position))
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if (dim(mean_duet_by_position) && dim(mean_affinity_by_position)){
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print(paste0("PASS: dim's match, mering dfs by column :", common_cols))
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#combined = as.data.frame(cbind(mean_duet_by_position, mean_affinity_by_position ))
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combined_df = as.data.frame(merge(mean_duet_by_position
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, mean_affinity_by_position
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, by = common_cols
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, all = T))
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cat(paste0("\nnrows combined_df:", nrow(combined_df)
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, "\nnrows combined_df:", ncol(combined_df)))
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}else{
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cat(paste0("FAIL: dim's mismatch, aborting cbind!"
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, "\nnrows df1:", nrow(mean_duet_by_position)
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, "\nnrows df2:", nrow(mean_affinity_by_position)))
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quit()
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}
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#%%============================================================
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# output
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write.csv(combined_df, outfile_mean_stability
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, row.names = F)
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cat("Finished writing file:\n"
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, outfile_mean_stability
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, "\nNo. of rows:", nrow(combined_df)
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, "\nNo. of cols:", ncol(combined_df))
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# end of script
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#===============================================================
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