136 lines
4.6 KiB
R
136 lines
4.6 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: To resolve ambiguous muts present in <gene>_metadata.csv
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#(which is one of the outputs from python script)
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# Input csv file: <gene>_metadata.csv
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# Output csv file: <gene>_metadata_clean.csv
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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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source("dirs.R")
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cat("Directories imported:"
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, "\n===================="
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, "\ndatadir:", datadir
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, "\nindir:", indir
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, "\noutdir:", outdir
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, "\nplotdir:", plotdir)
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cat("Variables imported:"
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, "\n====================="
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, "\ndrug:", drug
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, "\ngene:", gene
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, "\ngene_match:", gene_match
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, "\ndr_muts_col:", dr_muts_col
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, "\nother_muts_col:", other_muts_col
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, "\ndrtype_col:", resistance_col)
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#========================================================
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#===========
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# input
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#===========
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# infile1: gene associated meta data
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gene_metadata_raw = paste0(tolower(gene), "_metadata_raw.csv")
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infile_gene_metadata_raw = paste0(outdir, "/", gene_metadata_raw)
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cat("Input infile 1:", infile_gene_metadata_raw)
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# infile 2: ambiguous muts
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ambiguous_muts = paste0(tolower(gene), "_ambiguous_mut_names.csv")
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infile_ambiguous_muts = paste0(outdir, "/", ambiguous_muts)
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cat("Input infile 2:", infile_ambiguous_muts)
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#===========
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# output
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#===========
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# clean gene_metadat with ambiguous muts resolved
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gene_metadata_clean = paste0(tolower(gene), "_metadata.csv")
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outfile_gene_metadata_clean = paste0(outdir, "/", gene_metadata_clean)
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cat("Output file:", outfile_gene_metadata_clean)
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#%%===============================================================
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###########################
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# Read file: <gene>_meta data raw.csv
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###########################
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cat("Reading meta data file:", infile_gene_metadata_raw)
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gene_metadata_raw <- read.csv(infile_gene_metadata_raw
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, stringsAsFactors = F
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, header = T)
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cat("Dim:", dim(gene_metadata_raw))
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###########################
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# Read file: ambiguous muts.csv
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##########################
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ambiguous_muts = read.csv(infile_ambiguous_muts)
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ambiguous_muts_names = ambiguous_muts$mutation
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common_muts_all = gene_metadata_raw[gene_metadata_raw$mutation%in%ambiguous_muts_names,]
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#==============
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# resolving ambiguous muts
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#===============
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table(gene_metadata_raw$mutation_info)
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count_check = as.data.frame(cbind(table(gene_metadata_raw$mutationinformation, gene_metadata_raw$mutation_info)))
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count_check$checks = ifelse(count_check[[dr_muts_col]]&count_check[[other_muts_col]]>0
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, "ambi", "pass")
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table(count_check$checks)
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cat(table(count_check$checks)[["ambi"]], "ambiguous muts detected. Correcting these")
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# remove all ambiguous muts from df
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ids = gene_metadata_raw$mutation%in%common_muts_all$mutation; table(ids)
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gene_metadata_raw_unambiguous = gene_metadata_raw[!ids,]
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# sanity checks: should be true
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table(gene_metadata_raw_unambiguous$mutation%in%common_muts_all$mutation)[[1]] == nrow(gene_metadata_raw_unambiguous)
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nrow(gene_metadata_raw_unambiguous) + nrow(common_muts_all) == nrow(gene_metadata_raw)
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# check before resolving ambiguous muts
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table(common_muts_all$mutation_info)
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common_muts_all$mutation_info = as.factor(common_muts_all$mutation_info)
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# resolving ambiguous muts: change other_muts to dr_muts
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common_muts_all$mutation_info[common_muts_all$mutation_info==other_muts_col] <- dr_muts_col
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table(common_muts_all$mutation_info)
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common_muts_all$mutation_info = factor(common_muts_all$mutation_info)
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table(common_muts_all$mutation_info)
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common_muts_all$mutation_info = as.character(common_muts_all$mutation_info)
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# combining to a clean df
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gene_metadata = rbind(gene_metadata_raw_unambiguous, common_muts_all)
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all(dim(gene_metadata) == dim(gene_metadata))
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table(gene_metadata$mutation_info)
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count_check2 = as.data.frame(cbind(table(gene_metadata$mutationinformation
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, gene_metadata$mutation_info)))
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count_check2$checks = ifelse(count_check2[[dr_muts_col]]&count_check2[[other_muts_col]]>0
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, "ambi", "pass")
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if (table(count_check2$checks) == nrow(count_check2)){
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cat("PASS: ambiguous muts successfully resolved."
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, "\nwriting file")
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}else{
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print("FAIL: ambiguous muts could not be resolved!")
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quit()
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}
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#============
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# writing file
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#=============
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write.csv(gene_metadata, outfile_gene_metadata_clean
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, row.names = FALSE)
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#=====================================================================
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# End of script
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#======================================================================
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