minor changes to variable names in .R & .py
This commit is contained in:
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dd91692673
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2 changed files with 96 additions and 75 deletions
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@ -4,43 +4,41 @@
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# and add the calculated params to meta_data extracted from
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# pnca_data_extraction.py
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#===========================================
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homedir = '~'
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getwd()
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#setwd('~/git/LSHTM_analysis/meta_data_analysis')
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setwd(paste0(homedir, '/', 'git/LSHTM_analysis/meta_data_analysis'))
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setwd('~/git/LSHTM_analysis/meta_data_analysis')
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getwd()
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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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print(gene_match)
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cat(gene_match)
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#=======
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# input dir
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#=======
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# file1: Raw data
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# infile1: Raw data
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#indir = 'git/Data/pyrazinamide/input/original'
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indir = paste0('git/Data', '/', drug, '/', 'input/original')
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indir = paste0('~/git/Data')
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in_filename = 'original_tanushree_data_v2.csv'
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infile = paste0(homedir, '/', indir, '/', in_filename)
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print(paste0('Reading infile:', ' ', infile) )
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infile = paste0(indir, '/', in_filename)
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cat(paste0('Reading infile1: raw data', ' ', infile) )
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# file2: file to extract valid snps and add calcs to: pnca_metadata.csv {outfile3 from data extraction script}
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indir_metadata = paste0('git/Data', '/', drug, '/', 'output')
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# infile2: gene associated meta data file to extract valid snps and add calcs to
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# filename: outfile3 from data_extraction.py
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indir_metadata = paste0('~/git/Data', '/', drug, '/', 'output')
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in_filename_metadata = 'pnca_metadata.csv'
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infile_metadata = paste0(homedir, '/', indir_metadata, '/', in_filename_metadata)
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print(paste0('Reading metadata infile:', infile_metadata))
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infile_metadata = paste0(indir_metadata, '/', in_filename_metadata)
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cat(paste0('Reading infile2: gene associated metadata:', infile_metadata))
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#=========
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# output dir
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#=========
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# output filename in respective section at the time of outputting files
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# outdir = 'git/Data/pyrazinamide/output'
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outdir = paste0('git/Data', '/', drug, '/', 'output')
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outdir = paste0('~/git/Data', '/', drug, '/', 'output')
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out_filename = paste0(tolower(gene),'_', 'meta_data_with_AFandOR.csv')
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outfile = paste0(homedir, '/', outdir, '/', out_filename)
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print(paste0('Output file with full path:', outfile))
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outfile = paste0(outdir, '/', out_filename)
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cat(paste0('Output file with full path:', outfile))
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#%% end of variable assignment for input and output files
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@ -63,7 +61,7 @@ rm(indir, in_filename, infile)
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raw_data = raw_data[!is.na(raw_data$pyrazinamide),]
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total_samples = length(unique(raw_data$id))
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print(paste0('Total samples without NA in', ' ', drug, 'is:', total_samples))
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cat(paste0('Total samples without NA in', ' ', drug, 'is:', total_samples))
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# sanity check: should be true
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is.numeric(total_samples)
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@ -82,7 +80,7 @@ raw_data$all_muts_pnca = tolower(raw_data$all_mutations_pyrazinamide)
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# sanity checks
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#table(grepl("pnca_p",raw_data$all_muts_pnca))
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print(paste0('converting gene match:', gene_match, ' ', 'to lowercase'))
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cat(paste0('converting gene match:', gene_match, ' ', 'to lowercase'))
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gene_match = tolower(gene_match)
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table(grepl(gene_match,raw_data$all_muts_pnca))
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@ -109,7 +107,7 @@ table(mut, dst)
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#===============
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# Step 2: Read valid snps for which OR can be calculated (infile_comp_snps.csv)
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#===============
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print(paste0('Reading metadata infile:', infile_metadata))
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cat(paste0('Reading metadata infile:', infile_metadata))
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pnca_metadata = read.csv(infile_metadata
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# , file.choose()
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@ -118,8 +116,8 @@ pnca_metadata = read.csv(infile_metadata
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# clear variables
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rm(homedir, in_filename, indir, infile)
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rm(indir_metadata, infile_metadata, in_filename_metadata)
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rm(indir, in_filename, infile)
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rm(indir_metadata, in_filename_metadata, infile_metadata)
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# count na in pyrazinamide column
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tot_pza_na = sum(is.na(pnca_metadata$pyrazinamide))
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@ -130,15 +128,15 @@ pnca_snps_or = pnca_metadata[!is.na(pnca_metadata$pyrazinamide),]
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# sanity check
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if(nrow(pnca_snps_or) == expected_rows){
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print('PASS: no. of rows match with expected_rows')
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cat('PASS: no. of rows match with expected_rows')
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} else{
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print('FAIL: nrows mismatch.')
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cat('FAIL: nrows mismatch.')
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}
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# extract unique snps to iterate over for AF and OR calcs
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pnca_snps_unique = unique(pnca_snps_or$mutation)
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print(paste0('Total no. of distinct comp snps to perform OR calcs: ', length(pnca_snps_unique)))
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cat(paste0('Total no. of distinct comp snps to perform OR calcs: ', length(pnca_snps_unique)))
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# Define OR function
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x = as.numeric(mut)
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@ -192,38 +190,45 @@ hist(log(ors)
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# FIXME: could be good to add a sanity check
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if (table(names(ors) == names(pvals)) & table(names(ors) == names(afs)) & table(names(pvals) == names(afs)) == length(pnca_snps_unique)){
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print('PASS: names of ors, pvals and afs match: proceed with combining into a single df')
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cat('PASS: names of ors, pvals and afs match: proceed with combining into a single df')
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} else{
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print('FAIL: names of ors, pvals and afs mismatch')
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cat('FAIL: names of ors, pvals and afs mismatch')
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}
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# combine
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# combine ors, pvals and afs
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cat('Combining calculated params into a df: ors, pvals and afs')
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comb_AF_and_OR = data.frame(ors, pvals, afs)
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head(rownames(comb_AF_and_OR))
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cat('No. of rows in comb_AF_and_OR: ', nrow(comb_AF_and_OR)
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, '\nNo. of cols in comb_AF_and_OR: ', ncol(comb_AF_and_OR))
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cat('Rownames == mutation: ', head(rownames(comb_AF_and_OR)))
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# add rownames of comb_AF_and_OR as an extra column 'mutation' to allow merging based on this column
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comb_AF_and_OR$mutation = rownames(comb_AF_and_OR)
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# sanity check
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if (table(rownames(comb_AF_and_OR) == comb_AF_and_OR$mutation)){
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print('PASS: rownames and mutaion col values match')
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cat('PASS: rownames and mutaion col values match')
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}else{
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print('FAIL: rownames and mutation col values mismatch')
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cat('FAIL: rownames and mutation col values mismatch')
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}
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############
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# Merge 1:
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# Merge 1: combine meta data file with calculated num params
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###########
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df1 = pnca_metadata
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df2 = comb_AF_and_OR
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head(df1$mutation); head(df2$mutation)
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cat('checking commom col of the two dfs before merging:'
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,'\ndf1:', head(df1$mutation)
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, '\ndf2:', head(df2$mutation))
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# FIXME: newlines
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print(paste0('merging two dfs: '
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cat(paste0('merging two dfs: '
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,'\ndf1 (big df i.e. meta data) nrows: ', nrow(df1)
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,'\ndf2 (small df i.e af, or, pval) nrows: ', nrow(df2)
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, 'expected rows in merged df: ', nrow(df1), 'expected cols in merged_df: ', (ncol(df1) + ncol(df2) - 1)))
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,'\nexpected rows in merged df: ', nrow(df1)
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,'\nexpected cols in merged_df: ', (ncol(df1) + ncol(df2) - 1)))
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merged_df = merge(df1 # big file
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, df2 # small (afor file)
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@ -232,9 +237,9 @@ merged_df = merge(df1 # big file
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# sanity check
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if(ncol(merged_df) == (ncol(df1) + ncol(df2) - 1)){
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print(paste0('PASS: no. of cols is as expected: ', ncol(merged_df)))
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cat(paste0('PASS: no. of cols is as expected: ', ncol(merged_df)))
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} else{
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print('FAIL: no.of cols mistmatch')
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cat('FAIL: no.of cols mistmatch')
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}
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# quick check
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@ -243,18 +248,24 @@ merged_df[merged_df$mutation == i,]
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# count na in each column
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na_count = sapply(merged_df, function(y) sum(length(which(is.na(y))))); na_count
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# only some or and Af should be NA
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#Row.names ors pvals afs
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#63 63 63 63
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# check last three cols: should be NA
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if ( identical(na_count[[length(na_count)]], na_count[[length(na_count)-1]], na_count[[length(na_count)-2]])){
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cat('PASS: No. of NAs for OR, AF and Pvals are equal as expected',
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'\nNo. of NA: ', na_count[[length(na_count)]])
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} else {
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cat('FAIl: No. of NAs for OR, AF and Pvals mismatch')
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}
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# reassign custom colnames
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cat('Assigning custom colnames for the calculated params...')
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colnames(merged_df)[colnames(merged_df)== "ors"] <- "OR"
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colnames(merged_df)[colnames(merged_df)== "afs"] <- "AF"
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colnames(merged_df)[colnames(merged_df)== "pvals"] <- "pvalue"
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colnames(merged_df)[colnames(merged_df)== "afs"] <- "AF"
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colnames(merged_df)
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# add log OR and neglog pvalue
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# add 3 more cols: log OR, neglog pvalue and AF_percent cols
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merged_df$logor = log(merged_df$OR)
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is.numeric(merged_df$logor)
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@ -273,17 +284,22 @@ merged_df[merged_df$mutation == i,]
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# FIXME: harcoding (beware!), NOT FATAL though!
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ncol_added = 3
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print(paste0('Added', ncol_added, ' ', 'more cols to merged_df i.e log10 OR and -log10 P-val: '
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, 'no. of cols in merged_df now: ', ncol(merged_df)))
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cat(paste0('Added', ' ', ncol_added, ' more cols to merged_df:'
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, '\ncols added: logor, neglog10pvalue and AF_percent:'
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, '\nno. of cols in merged_df now: ', ncol(merged_df)))
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#%% write file out: pnca_meta_data_with_AFandOR
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print(paste0('writing output file in: '
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, 'Filename: ', out_filename
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, 'Path:', outdir))
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cat(paste0('writing output file: '
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, '\nFilename: ', out_filename
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, '\nPath:', outdir))
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write.csv(merged_df, outfile
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, row.names = F)
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print(paste0('Finished writing:', out_filename, '\nExpected no. of cols:', ncol(merged_df)))
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print('======================================================================')
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cat(paste0('Finished writing:'
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, out_filename
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, '\nNo. of rows: ', nrow(merged_df)
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, '\nNo. of cols: ', ncol(merged_df)))
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cat('======================================================================')
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rm(out_filename)
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@ -14,7 +14,7 @@ Created on Tue Aug 6 12:56:03 2019
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# load libraries
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import os, sys
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import pandas as pd
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import numpy as np
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#import numpy as np
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#from pandas.api.types import is_string_dtype
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#from pandas.api.types import is_numeric_dtype
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@ -61,21 +61,21 @@ gene_match = gene + '_p.'
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# input dir
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#=======
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#indir = 'git/Data/pyrazinamide/input/original'
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indir = 'git/Data' + '/' + drug + '/' + 'input/original'
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indir = homedir + '/' + 'git/Data'
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#=========
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# output dir
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#=========
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# several output files
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# output filenames in respective sections at the time of outputting files
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#outdir = 'git/Data/pyrazinamide/output'
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outdir = 'git/Data' + '/' + drug + '/' + 'output'
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outdir = homedir + '/' + 'git/Data' + '/' + drug + '/' + 'output'
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#%%end of variable assignment for input and output files
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#==============================================================================
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#%% Read files
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in_filename = 'original_tanushree_data_v2.csv'
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infile = homedir + '/' + indir + '/' + in_filename
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infile = indir + '/' + in_filename
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print('Reading input master file:', infile)
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master_data = pd.read_csv(infile, sep = ',')
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@ -325,12 +325,12 @@ print('======================================================================')
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#%% write file
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#print(outdir)
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out_filename0 = gene.lower() + '_' + 'common_ids.csv'
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outfile0 = homedir + '/' + outdir + '/' + out_filename0
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outfile0 = outdir + '/' + out_filename0
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#FIXME: CHECK line len(common_ids)
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print('Writing file: common ids:',
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'\nFilename:', out_filename0,
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'\nPath:', homedir +'/'+ outdir,
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'\nPath:', outdir,
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'\nExpected no. of rows:', len(common_ids) )
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common_ids.to_csv(outfile0)
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@ -690,7 +690,7 @@ print('Counting no. of ambiguous muts...')
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if dr_muts[dr_muts.isin(other_muts)].nunique() == other_muts[other_muts.isin(dr_muts)].nunique():
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common_muts = dr_muts[dr_muts.isin(other_muts)].value_counts().keys().tolist()
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print('No. of ambigiuous muts detected:'+ str(len(common_muts)),
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print('Distinct no. of ambigiuous muts detected:'+ str(len(common_muts)),
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'list of ambiguous mutations (see below):', *common_muts, sep = '\n')
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else:
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print('Error: ambiguous muts detected, but extraction failed. Debug!',
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@ -711,21 +711,27 @@ del(c1, c2, col_to_split1, col_to_split2, comp_pnca_samples, dr_WF0, dr_df, dr_m
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#other_muts.to_csv('other_muts.csv', header = True)
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out_filename1 = gene.lower() + '_' + 'ambiguous_muts.csv'
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outfile1 = homedir + '/' + outdir + '/' + out_filename1
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outfile1 = outdir + '/' + out_filename1
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print('Writing file: ambiguous muts',
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'\nFilename:', out_filename1,
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'\nPath:', homedir +'/'+ outdir)
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'\nPath:', outdir)
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#common_muts = ['pncA_p.Val180Phe','pncA_p.Gln10Pro'] # test
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inspect = pnca_LF1[pnca_LF1['mutation'].isin(common_muts)]
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inspect.to_csv(outfile1)
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print('Finished writing:', out_filename1, '\nExpected no. of rows (no. of samples with the ambiguous muts present):', dr_muts.isin(other_muts).sum() + other_muts.isin(dr_muts).sum())
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print('Finished writing:', out_filename1,
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'\nNo. of rows:', len(inspect),
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'\nNo. of cols:', len(inspect.columns),
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'\nNo. of rows = no. of samples with the ambiguous muts present:', dr_muts.isin(other_muts).sum() + other_muts.isin(dr_muts).sum())
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print('======================================================================')
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del(out_filename1)
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#%%
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#%% read aa dict and pull relevant info
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print('Reading aa dict and fetching1 letter aa code',
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'\nFormatting mutation in mCSM style format: {WT}<POS>{MUT}',
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'\nAdding aa properties')
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#===========
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# Split 'mutation' column into three: wild_type, position and
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# mutant_type separately. Then map three letter code to one using
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@ -733,7 +739,6 @@ del(out_filename1)
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# First: Import reference dict
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# Second: convert to mutation to lowercase for compatibility with dict
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#===========
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from reference_dict import my_aa_dict # CHECK DIR STRUC THERE!
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pnca_LF1['mutation'] = pnca_LF1.loc[:, 'mutation'].str.lower()
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#=======
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# Iterate through the dict, create a lookup dict i.e
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@ -756,7 +761,7 @@ pnca_LF1['position'] = pnca_LF1['mutation'].str.extract(r'(\d+)')
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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print('======================================================================')
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#print('======================================================================')
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#=========
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# iterate through the dict, create a lookup dict that i.e
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# lookup_dict = {three_letter_code: aa_prop_water}
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@ -777,7 +782,7 @@ for k, v in my_aa_dict.items():
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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print('======================================================================')
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#print('======================================================================')
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#========
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# iterate through the dict, create a lookup dict that i.e
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# lookup_dict = {three_letter_code: aa_prop_polarity}
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@ -798,7 +803,7 @@ for k, v in my_aa_dict.items():
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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print('======================================================================')
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#print('======================================================================')
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#========
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# iterate through the dict, create a lookup dict that i.e
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@ -866,12 +871,12 @@ else:
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print('======================================================================')
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out_filename2 = gene.lower() + '_' + 'mcsm_snps.csv'
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outfile2 = homedir + '/' + outdir + '/' + out_filename2
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outfile2 = outdir + '/' + out_filename2
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print('Writing file: mCSM style muts',
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'\nFilename:', out_filename2,
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'\nPath:', homedir +'/'+ outdir,
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'\nmutation format (SNP): {Wt}<POS>{Mut}',
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'\nPath:', outdir,
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'\nmutation format (SNP): {WT}<POS>{MUT}',
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'\nNo. of distinct muts:', len(snps_only),
|
||||
'\nNo. of distinct positions:', len(pos_only))
|
||||
|
||||
|
|
@ -887,10 +892,10 @@ del(out_filename2)
|
|||
#%% Write file: pnca_metadata (i.e pnca_LF1)
|
||||
# where each row has UNIQUE mutations NOT unique sample ids
|
||||
out_filename3 = gene.lower() + '_' + 'metadata.csv'
|
||||
outfile3 = homedir + '/' + outdir + '/' + out_filename3
|
||||
outfile3 = outdir + '/' + out_filename3
|
||||
print('Writing file: LF formatted data',
|
||||
'\nFilename:', out_filename3,
|
||||
'\nPath:', homedir +'/'+ outdir)
|
||||
'\nPath:', outdir)
|
||||
|
||||
pnca_LF1.to_csv(outfile3, header = True, index = False)
|
||||
print('Finished writing:', out_filename3,
|
||||
|
|
@ -929,12 +934,12 @@ else:
|
|||
print('======================================================================')
|
||||
|
||||
out_filename4 = gene.lower() + '_' + 'all_muts_msa.csv'
|
||||
outfile4 = homedir + '/' + outdir + '/' + out_filename4
|
||||
outfile4 = outdir + '/' + out_filename4
|
||||
|
||||
print('Writing file: mCSM style muts for msa',
|
||||
'\nFilename:', out_filename4,
|
||||
'\nPath:', homedir +'/'+ outdir,
|
||||
'\nmutation format (SNP): {Wt}<POS>{Mut}',
|
||||
'\nPath:', outdir,
|
||||
'\nmutation format (SNP): {WT}<POS>{MUT}',
|
||||
'\nNo.of lines of msa:', len(all_muts_msa),
|
||||
)
|
||||
|
||||
|
|
@ -961,12 +966,12 @@ pos_only.position.dtype
|
|||
pos_only_sorted = pos_only.sort_values(by = 'position', ascending = True)
|
||||
|
||||
out_filename5 = gene.lower() + '_' + 'mutational_positons.csv'
|
||||
outfile5 = homedir + '/' + outdir + '/' + out_filename5
|
||||
outfile5 = outdir + '/' + out_filename5
|
||||
|
||||
print('Writing file: mutational positions',
|
||||
'\nNo. of distinct positions:', len(pos_only_sorted),
|
||||
'\nFilename:', out_filename5,
|
||||
'\nPath:', homedir +'/'+ outdir)
|
||||
'\nPath:', outdir)
|
||||
|
||||
pos_only_sorted.to_csv(outfile5, header = True, index = False)
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue