work from thinkpad
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4d03a43c4a
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660ab31ce8
2 changed files with 86 additions and 65 deletions
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@ -81,8 +81,8 @@ indir = args.input_dir
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outdir = args.output_dir
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make_dirs = args.make_dirs
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#drug = 'ethambutol'
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#gene = 'embB'
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#drug = 'streptomycin'
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#gene = 'gid'
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#%% input and output dirs and files
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#=======
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@ -122,15 +122,15 @@ if make_dirs:
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# handle missing dirs here
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if not os.path.isdir(datadir):
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print('ERROR: Data directory does not exist:', datadir
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, '\nPlease create and ensure gwas data is present and then rerun\nelse specify cmd option ---make_dirs')
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, '\nPlease create and ensure gwas data is present and then rerun\nelse specify cmd option --make_dirs')
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sys.exit()
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if not os.path.isdir(indir):
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print('ERROR: Input directory does not exist:', indir
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, '\nPlease either create or specify indir and rerun\nelse specify cmd option ---make_dirs')
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, '\nPlease either create or specify indir and rerun\nelse specify cmd option --make_dirs')
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sys.exit()
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if not os.path.isdir(outdir):
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print('ERROR: Output directory does not exist:', outdir
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, '\nPlease create or specify outdir and rerun\nelse specify cmd option ---make_dirs')
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, '\nPlease create or specify outdir and rerun\nelse specify cmd option --make_dirs')
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sys.exit()
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# Requires
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@ -317,7 +317,7 @@ for i, id in enumerate(clean_df.id):
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print('RESULTS:')
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print('Total WT in dr_muts_col:', wt)
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print('Total matches of', gene, 'SNP matches in', dr_muts_col, ':', dr_gene_count)
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print('Total samples with > 1', gene, 'muts in dr_muts_col:', len(id2_dr) )
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print('Total samples with > 1', gene, 'nsSNPs in dr_muts_col:', len(id2_dr) )
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print('=================================================================')
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del(clean_df, na_count, i, id, wt, id2_dr, count_gene_dr, count_wt)
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@ -361,7 +361,7 @@ for i, id in enumerate(clean_df.id):
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print('RESULTS:')
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print('Total WT in other_muts_col:', wt_other)
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print('Total matches of', gene, 'SNP matches in', other_muts_col, ':', other_gene_count)
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print('Total samples with > 1', gene, 'muts in other_muts_col:', len(id2_other) )
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print('Total samples with > 1', gene, 'nsSNPs in other_muts_col:', len(id2_other) )
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print('=================================================================')
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print('Predicting total no. of rows in the curated df:', dr_gene_count + other_gene_count
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@ -851,7 +851,7 @@ else:
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, '\nMuts are unique to dr_ and other_ mutation class'
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, '\n=========================================================')
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# inspect dr_muts and other muts
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# inspect dr_muts and other muts: Fixed in case no ambiguous muts detected!
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if dr_muts.isin(other_muts).sum() & other_muts.isin(dr_muts).sum() > 0:
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print('Finding ambiguous muts...'
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, '\n========================================================='
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@ -861,24 +861,37 @@ if dr_muts.isin(other_muts).sum() & other_muts.isin(dr_muts).sum() > 0:
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, '\nTotal no. of samples in other_muts present in dr_muts:', other_muts.isin(dr_muts).sum()
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, '\nThese are:\n', other_muts[other_muts.isin(dr_muts)]
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, '\n=========================================================')
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else:
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sys.exit('Error: ambiguous muts present, but extraction failed. Debug!')
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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('Distinct no. of ambigiuous muts detected:'+ str(len(common_muts))
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, '\nlist of ambiguous mutations (see below):', *common_muts, sep = '\n')
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print('\n===========================================================')
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else:
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print('Error: ambiguous muts detected, but extraction failed. Debug!'
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print('Counting no. of ambiguous muts...'
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, '\nNo. of ambiguous muts in dr:'
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, len(dr_muts[dr_muts.isin(other_muts)].value_counts().keys().tolist())
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, '\nNo. of ambiguous muts in other:'
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, len(other_muts[other_muts.isin(dr_muts)].value_counts().keys().tolist())
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, '\n=========================================================')
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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('Distinct no. of ambigiuous muts detected:'+ str(len(common_muts))
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, '\nlist of ambiguous mutations (see below):', *common_muts, sep = '\n')
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print('\n===========================================================')
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else:
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#sys.exit('Error: ambiguous muts present, but extraction failed. Debug!')
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print('No: ambiguous muts present')
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#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('Distinct no. of ambigiuous muts detected:'+ str(len(common_muts))
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# , '\nlist of ambiguous mutations (see below):', *common_muts, sep = '\n')
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# print('\n===========================================================')
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#else:
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# print('Error: ambiguous muts detected, but extraction failed. Debug!'
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# , '\nNo. of ambiguous muts in dr:'
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# , len(dr_muts[dr_muts.isin(other_muts)].value_counts().keys().tolist())
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# , '\nNo. of ambiguous muts in other:'
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# , len(other_muts[other_muts.isin(dr_muts)].value_counts().keys().tolist())
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# , '\n=========================================================')
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#%% clear variables
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del(id_dr, id_other
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#, meta_data
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@ -893,25 +906,24 @@ del(c1, c2, col_to_split1, col_to_split2, comp_gene_samples, dr_WF0, dr_df, dr_m
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#print(outdir)
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#dr_muts.to_csv('dr_muts.csv', header = True)
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#other_muts.to_csv('other_muts.csv', header = True)
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out_filename_ambig_muts = gene.lower() + '_ambiguous_muts.csv'
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outfile_ambig_muts = outdir + '/' + out_filename_ambig_muts
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print('\n----------------------------------'
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if dr_muts.isin(other_muts).sum() & other_muts.isin(dr_muts).sum() > 0:
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out_filename_ambig_muts = gene.lower() + '_ambiguous_muts.csv'
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outfile_ambig_muts = outdir + '/' + out_filename_ambig_muts
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print('\n----------------------------------'
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, '\nWriting file: ambiguous muts'
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, '\n----------------------------------'
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, '\nFilename:', outfile_ambig_muts)
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inspect = gene_LF1[gene_LF1['mutation'].isin(common_muts)]
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inspect.to_csv(outfile_ambig_muts, index = False)
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inspect = gene_LF1[gene_LF1['mutation'].isin(common_muts)]
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inspect.to_csv(outfile_ambig_muts, index = False)
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print('Finished writing:', out_filename_ambig_muts
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print('Finished writing:', out_filename_ambig_muts
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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:'
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, dr_muts.isin(other_muts).sum() + other_muts.isin(dr_muts).sum()
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, '\n=============================================================')
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del(out_filename_ambig_muts)
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del(out_filename_ambig_muts)
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#%% end of data extraction and some files writing. Below are some more files writing.
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#=============================================================================
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#%% Formatting df: read aa dict and pull relevant info
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@ -1181,7 +1193,7 @@ if snps_only.mutationinformation.isna().sum() == 0:
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else:
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sys.exit('FAIL: SNP has NA, Possible mapping issues from dict?')
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out_filename_mcsmsnps = gene.lower() + '_mcsm_snps.csv'
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out_filename_mcsmsnps = gene.lower() + '_mcsm_style_snps.csv'
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outfile_mcsmsnps = outdir + '/' + out_filename_mcsmsnps
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print('\n----------------------------------'
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@ -1215,7 +1227,7 @@ metadata_pos.sort_values(by = ['meta_pos_count'], ascending = False, inplace = T
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out_filename_metadata_poscounts = gene.lower() + '_metadata_poscounts.csv'
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outfile_metadata_poscounts = outdir + '/' + out_filename_metadata_poscounts
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print('\n----------------------------------'
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, 'Writing file: Metadata poscounts'
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, '\nWriting file: Metadata poscounts'
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, '\n----------------------------------'
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, '\nFile:', outfile_metadata_poscounts
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, '\n============================================================')
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@ -1309,7 +1321,7 @@ out_filename_pos = gene.lower() + '_mutational_positons.csv'
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outfile_pos = outdir + '/' + out_filename_pos
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print('\n----------------------------------'
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, 'Writing file: mutational positions'
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, '\nWriting file: mutational positions'
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, '\n----------------------------------'
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, '\nFile:', outfile_pos
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, '\nNo. of distinct positions:', len(pos_only_sorted)
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@ -1349,15 +1361,14 @@ print('============================================'
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, '\nTotal no. of samples with missense muts:', len(gene_LF1)
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, '\nTotal no. of unique samples with missense muts:', gene_LF1['id'].nunique()
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, '\n'
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, '\nTotal no.of samples with common_ids:', nu_common_ids['id']
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, '\nTotal no.of samples with ambiguous muts:', len(inspect)
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, '\nTotal no.of samples with common_ids:', nu_common_ids['id'])
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if dr_muts.isin(other_muts).sum() & other_muts.isin(dr_muts).sum() > 0:
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print('\nTotal no.of samples with ambiguous muts:', len(inspect)
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#, '\nTotal no.of unique ambiguous muts:', len(common_muts)
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, '\nTotal no.of unique ambiguous muts:', inspect['mutation'].nunique()
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, '\n============================================================='
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, '\n\n\n')
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#=======================================================================
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print(u'\u2698' * 50,
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'\nEnd of script: Data extraction and writing files'
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@ -1,32 +1,42 @@
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#========
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# data extraction: Must be run first to extract mutations for each drug-gene combination
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#========
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./data_extraction.py -d pyrazinamide -g pncA
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./data_extraction.py -d <drug> -g <gene> --make_dirs
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#========
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# add chains to a PDB file: for modeller models lack chain ID, this script is used
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#========
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add_chains_pdb.py <N> MY_PDB.pdb
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#========
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# pdb data extraction: To find out discontinuity of chain and removing invalid muts to allow foldx and mcsm to run properly!
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#========
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In progress...
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#========
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# foldx: specify chain if default is NOT 'A'
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#========
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./runFoldx.py -d pyrazinamide -g pncA
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./runFoldx.py -d <drug> -g <gene> -c1 A -p /media/tanu/eb1d072a-3f73-427f-aeb8-f6852b5c5216/Data/processing
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#========
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# mcsm: specify chain if default is NOT 'A'
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#========
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./run_mcsm.py -d pyrazinamide -g pncA -s submit -l PZA --debug
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./run_mcsm.py -d pyrazinamide -g pncA -s get
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./run_mcsm.py -d pyrazinamide -g pncA -s format
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./run_mcsm.py -d <drug> -g <gene> -s submit -l PZA --debug
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./run_mcsm.py -d <drug> -g <gene> pncA -s get
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./run_mcsm.py -d <drug> -g <gene> pncA -s format
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#====================
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# other struct params
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#====================
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./dssp_df.py -d pyrazinamide -g pncA
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./dssp_df.py -d <drug> -g <gene>
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# Errors on matplot.lib warn=, so just comment it out for the timebeing!: MONKEY PATCH
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./kd_df.py -d pyrazinamide -g pncA -fasta # fixme: NO of cols says 2, but is actually 3
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./rd_df.py -d pyrazinamide -g pncA # fixme: input tsv file is sourced manually from website!
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./kd_df.py -d <drug> -g <gene> -fasta # fixme: NO of cols says 2, but is actually 3
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./rd_df.py -d <drug> -g <gene> # fixme: input tsv file is sourced manually from website!
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#==============================
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# af_or calcs: different types
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#==============================
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./af_or_calcs.R --d pyrazinamide --gene pncA # fixme: No conditional dir structure
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./af_or_calcs.R -d <drug> -g <gene># fixme: No conditional dir structure
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#==============================
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# af_or calcs: kinship
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@ -40,18 +50,18 @@ USE THE BELOW from within the or_kinship_link.py script or something?! as part o
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# for now use the file already created using some manual wrestling to link
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# the OR for kinship with mutations
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./or_kinship_link.py -d pyrazinamide -g pncA -sc 2288681 -ec 2289241
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./or_kinship_link.py -d <drug> -g <gene> -sc <start_coord> -ec <end_coord>
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#==============================
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# formatting: ns<gene>_snp_info.txt
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#==============================
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# This adds mcsm style muts
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./snpinfo_format.py -d pyrazinamide -g pncA
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./snpinfo_format.py -d <drug> -g <gene>
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#==============================
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# combining dfs: combining_dfs.py
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#==============================
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# FIXME: combining_FIXME.py
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./combining_dfs.py -d pyrazinamide -g pncA
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./combining_dfs.py --d <drug> -g <gene>
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