163 lines
4.5 KiB
R
163 lines
4.5 KiB
R
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("Header_TT.R")
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require(data.table)
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require(dplyr)
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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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#========================================================
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#%% variable assignment: input and output paths & filenames
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drug = "pyrazinamide"
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gene = "pncA"
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gene_match = paste0(gene,"_p.")
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cat(gene_match)
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#=============
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# directories
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#=============
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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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#======
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# input
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#======
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#in_filename = "mcsm_complex1_normalised.csv"
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in_filename_params = paste0(tolower(gene), "_all_params.csv")
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infile_params = paste0(outdir, "/", in_filename_params)
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cat(paste0("Input file 1:", infile_params) )
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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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# Read file: struct params
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###########################
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cat("Reading struct params including mcsm:", in_filename_params)
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my_df = read.csv(infile_params
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#, stringsAsFactors = F
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, header = T)
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cat("Input dimensions:", dim(my_df))
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# clear variables
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rm(in_filename_params, infile_params)
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# quick checks
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colnames(my_df)
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str(my_df)
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# check for duplicate mutations
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if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformation)){
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cat(paste0("CAUTION:", " Duplicate mutations identified"
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, "\nExtracting these..."))
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dup_muts = my_df[duplicated(my_df$mutationinformation),]
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dup_muts_nu = length(unique(dup_muts$mutationinformation))
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cat(paste0("\nDim of duplicate mutation df:", nrow(dup_muts)
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, "\nNo. of unique duplicate mutations:", dup_muts_nu
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, "\n\nExtracting df with unique mutations only"))
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my_df_u = my_df[!duplicated(my_df$mutationinformation),]
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}else{
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cat(paste0("No duplicate mutations detected"))
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my_df_u = my_df
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}
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upos = unique(my_df_u$position)
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cat("Dim of clean df:")
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cat(dim(my_df_u))
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cat("\nNo. of unique mutational positions:"); cat(length(upos))
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########################################################################
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# end of data extraction and cleaning for plots #
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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 average
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# Lig average
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###########################
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head(df$position); head(df$mutationinformation)
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head(df$duet_scaled)
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# order data frame
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#df = df[order(df$position),] #already done
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head(df$position); head(df$mutationinformation)
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head(df$duet_scaled)
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#***********
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# PS: average by position
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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_scaled))
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#***********
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# Lig: average by position
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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(affinity_scaled))
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#***********
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# cbind:mean_duet_by_position and mean_affinity_by_position
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#***********
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combined = as.data.frame(cbind(mean_duet_by_position, mean_affinity_by_position ))
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# sanity check
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# mean_PS_affinity_Bfactor
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colnames(combined)
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colnames(combined) = c("position"
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, "average_duet_scaled"
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, "position2"
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, "average_affinity_scaled")
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colnames(combined)
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identical(combined$position, combined$position2)
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n = which(colnames(combined) == "position2"); n
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combined_df = combined[,-n]
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max(combined_df$average_duet_scaled) ; min(combined_df$average_duet_scaled)
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max(combined_df$average_affinity_scaled) ; min(combined_df$average_affinity_scaled)
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head(combined_df$position); tail(combined_df$position)
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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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