saving data extraction with final processing
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3c436f0c27
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1 changed files with 42 additions and 35 deletions
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@ -71,7 +71,7 @@ arg_parser.add_argument('-g', '--gene', help='gene name (case sensitive)', defau
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arg_parser.add_argument('--datadir', help = 'Data Directory. By default, it assmumes homedir + git/Data')
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arg_parser.add_argument('-i', '--input_dir', help = 'Input dir containing pdb files. By default, it assmumes homedir + <drug> + input')
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arg_parser.add_argument('-o', '--output_dir', help = 'Output dir for results. By default, it assmes homedir + <drug> + output')
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arg_parser.add_argument('-m', '--make_dirs', help = 'Make dir for input and output', action='store_true')
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arg_parser.add_argument('-m', '--make_dirs', help = 'Make dir for Data, input and output', action='store_true')
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arg_parser.add_argument('--debug', action ='store_true', help = 'Debug Mode')
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@ -925,9 +925,9 @@ changes_dict = {}
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##BROKENNNN!!!!
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common_muts
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gene_LF1['mutation'].head()
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common_muts_lower = list((map(lambda x: x.lower(), common_muts)))
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common_muts_lower
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##BROKENNNN!!!!
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#common_muts_lower = list((map(lambda x: x.lower(), common_muts)))
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#common_muts_lower
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for i in common_muts:
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#for i in common_muts_lower:
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#print(i)
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@ -992,8 +992,7 @@ print('\n----------------------------------'
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ambiguous_muts_value_counts.to_csv(outfile_ambig_mut_counts, index = True)
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#%% FIXME: Add sanity check to make sure you can add value_count checks
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#%% Resolving ambiguous muts
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# Merging ambiguous muts
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#%% Resolving ambiguous muts: Merging ambiguous muts with the revised annotations
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#=================
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# Merge ambig muts
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# with gene_LF1
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@ -1034,7 +1033,7 @@ gene_LF1['mutation_info'].value_counts()
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# reassign
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#%% PHEW! Good to go for downstream stuff
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#%% Add column: Mutationinformation
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#%% Add column: Mutationinformation ==> gene_LF1
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# splitting mutation column to get mCSM style muts
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#=====================================================
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# Formatting df: read aa dict and pull relevant info
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@ -1098,7 +1097,8 @@ for k, v in my_aa_dict.items():
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#gene_LF1['position'] = gene_LF1['mutation'].str.extract(r'(\d+)')
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gene_LF1['position'] = gene_LF1['mutation'].str.extract(pos_regex)
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mylen1 = len(gene_LF1.columns)
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#mylen1 = len(gene_LF1.columns)
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mylen0_v2 = len(gene_LF1.columns)
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# sanity checks
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print('checking if 3-letter wt&mut residue extraction worked correctly')
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@ -1115,14 +1115,15 @@ else:
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, '\nmutant-type\n', mut
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, '\ndim of df:', gene_LF1.shape)
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if mylen1 == mylen0 + ncol_mutf_add:
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#if mylen1 == mylen0 + ncol_mutf_add:
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if mylen0_v2 == mylen0 + ncol_mutf_add:
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print('PASS: successfully added', ncol_mutf_add, 'cols'
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, '\nold length:', mylen0
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, '\nnew len:', mylen1)
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, '\nnew len:', mylen0_v2)
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else:
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print('FAIL: failed to add cols:'
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, '\nold length:', mylen0
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, '\nnew len:', mylen1)
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, '\nnew len:', mylen0_v2)
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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@ -1145,17 +1146,20 @@ gene_LF1['position'] = pd.to_numeric(gene_LF1['position'])
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# sort by position inplace
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foo = gene_LF1['position'].value_counts()
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foo
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foo = foo.sort_index()
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gene_LF1.sort_values(by = ['position'], inplace = True)
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bar = gene_LF1['position'].value_counts()
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bar = bar.sort_index()
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if all(foo == bar):
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print('PASS: df ordered by position')
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print(gene_LF1['position'].head())
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else:
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sys.exit('FAIL: df could not be ordered. Check source')
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print('\nDim of gene_LF1:', len(gene_LF1.columns), 'more cols:\n')
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# FIXME:Can only compare identically-labeled Series objects
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#if (foo == bar).all():
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# print('PASS: df ordered by position')
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# print(gene_LF1['position'].head())
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#else:
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# print('FAIL: df could not be ordered. Check source')
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# sys.exit()
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#%% Create a copy of mutationinformation column for downstream mergeing
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gene_LF1['Mut'] = gene_LF1['mutationinformation']
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gene_LF1['Mut_copy'] = gene_LF1['mutationinformation']
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@ -1185,8 +1189,12 @@ gene_LF1['pos_count'] = gene_LF1['position'].map(z1)
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#test_df2 = test_df.loc[test_df['position'] == 10]
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###############################################################################
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cols_added = ['Mut', 'Mut_copy', 'index', 'index_copy', 'pos_count', 'snp_frequency']
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print('\nAdded', len(cols_added), 'more cols:\n'
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, '\nDim of new gene_LF1:', len(gene_LF1.columns))
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mylen1 = len(gene_LF1.columns) # updated my_len1
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###############################################################################
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#%% Add column: aa property_water
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#%% Add column: aa property_water ==> gene_LF1
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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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@ -1235,7 +1243,7 @@ else:
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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#%% Add column: aa_prop_polarity
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#%% Add column: aa_prop_polarity ==> gene_LF1
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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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@ -1283,7 +1291,7 @@ else:
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# clear variables
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del(k, v, wt, mut, lookup_dict)
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#%% Add column: aa_calcprop
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#%% Add column: aa_calcprop ==> gene_LF1
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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_calcprop}
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@ -1923,12 +1931,12 @@ print('Finished writing:', outfile_pos
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, '\nNo. of rows:', len(pos_only_sorted)
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, '\nNo. of cols:', len(pos_only_sorted.columns)
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, '\n============================================================='
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, '\n\n\n')
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, '\n')
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del(out_filename_pos)
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###############################################################################
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#%% Quick summary output
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print('============================================'
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print('\n============================================'
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, '\nQuick summary output for', drug, 'and' , gene.lower()
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, '\n============================================'
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, '\nTotal samples:', total_samples
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@ -1942,18 +1950,17 @@ print('============================================'
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, '\nPercentage of Sus and Res [Revised]', drug, 'samples:\n', gene_LF4['dst_mode'].value_counts(normalize = True)*100
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, '\n'
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, '\nTotal no. of unique snps:', len(snps_only)
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, '\nTotal no. of unique snps:', dr_muts_rev.nunique()+other_muts_rev.nunique()
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, '\nTotal no. of unique nsSNPs [check1: length of snps_only]:', len(snps_only)
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, '\nTotal no.of unique dr muts:', dr_muts_rev.nunique() # ADD
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, '\nTotal no.of unique other muts:', other_muts_rev.nunique()#ADD
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, '\nTotal no.of unique dr muts:' , dr_muts_rev.nunique()
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, '\nTotal no.of unique other muts:' , other_muts_rev.nunique()
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, '\nTotal no. of unique nsSNPs [check2: dr_muts + other_muts]:', dr_muts_rev.nunique()+other_muts_rev.nunique()
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, '\nTotal no.of unique missense muts:', gene_LF4['mutationinformation'].nunique()
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, '\nTotal no.of unique nSNSPs [check3, gene_LF4]:', gene_LF4['mutationinformation'].nunique()
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, '\nTotal no.of unique positions associated with missense muts:', gene_LF4['position'].nunique()
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, '\nTotal no. of samples with missense muts:', len(gene_LF4)
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, '\nTotal no. of unique samples with missense muts:', gene_LF4['id'].nunique()
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, '\n')
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, '\nTotal no. of samples with nsSNPs:', len(gene_LF4)
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, '\nTotal no. of unique sample ids with nsSNPs:', gene_LF4['id'].nunique()
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)
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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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