finally added all the lineage calculations
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1 changed files with 177 additions and 30 deletions
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@ -240,6 +240,16 @@ meta_data['lineage'].value_counts()
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meta_data['lineage'].value_counts().sum()
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meta_data['lineage'].nunique()
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# replace lineage with 'L' in lineage_labels
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#meta_data['lineage_labels'] = meta_data['lineage']
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#meta_data['lineage_labels'].equals(meta_data['lineage'])
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#all(meta_data['lineage_labels'].value_counts() == meta_data['lineage'].value_counts())
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#meta_data['lineage_labels'] = meta_data['lineage_labels'].str.replace('lineage', 'L')
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#meta_data['lineage'].value_counts()
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#meta_data['lineage_labels'].value_counts()
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meta_data['lineage'] = meta_data['lineage'].str.replace('lineage', 'L')
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meta_data['id'].nunique()
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meta_data['sample'].nunique()
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meta_data['id'].equals(meta_data['sample'])
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@ -523,7 +533,6 @@ del(out_filename_cid)
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# clear variables
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del(dr_id, other_id, meta_data_dr, meta_data_other, common_ids, common_mut_ids, common_ids2)
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#%% Extract gene specific nsSNPs: all nsSNPs i.e.'nssnp_match'
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print('Extracting nsSNP match:', gene, 'mutations from cols:\n'
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, dr_muts_col, 'and', other_muts_col, 'using string match:'
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@ -911,9 +920,9 @@ ambiguous_muts_value_counts
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gene_LF1_orig = gene_LF1.copy()
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gene_LF1_orig.equals(gene_LF1)
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# copy the old column for checking
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# copy the old columns for checking
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gene_LF1['mutation_info_orig'] = gene_LF1['mutation_info']
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gene_LF1['mutation_info_orig'].value_counts()
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gene_LF1['mutation_info_v1'] = gene_LF1['mutation_info']
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gene_LF1['mutation_info'].value_counts()
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#=====================================
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@ -956,22 +965,23 @@ changes_val
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changes_total = sum(changes_val)
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changes_dict
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# TODO: Add sanity check to make sure you can add value_count checks
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#%%FIXME: TODO: Add sanity check to make sure you can add value_count checks
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#%% Merging ambiguous muts
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#=================
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# Merge ambig muts
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# with gene_LF1
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#===================
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ambig_muts_rev_df.index
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gene_LF1.index
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all(ambig_muts_rev_df.index.isin(gene_LF1.index))
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gene_LF1.loc[ambig_muts_rev_df.index, 'mutation_info'] = ambig_muts_rev_df['mutation_info_REV']
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gene_LF1.loc[ambig_muts_rev_df.index, 'mutation_info_v1'] = ambig_muts_rev_df['mutation_info_REV']
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gene_LF1['mutation_info_orig'].value_counts()
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gene_LF1['mutation_info'].value_counts()
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gene_LF1['mutation_info_v1'].value_counts()
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foo = gene_LF1.iloc[ambig_muts_rev_df.index]
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foo[['mutation', 'mutation_info', 'mutation_info_orig']]
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# Sanity check1: if there are still any ambiguous muts
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muts_split_rev = list(gene_LF1.groupby('mutation_info'))
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muts_split_rev = list(gene_LF1.groupby('mutation_info_v1'))
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dr_muts_rev = muts_split_rev[0][1].mutation
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other_muts_rev = muts_split_rev[1][1].mutation
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print('splitting muts by mut_info:', muts_split_rev)
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@ -981,7 +991,7 @@ print('no. of other_muts samples', len(other_muts_rev))
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if not dr_muts_rev.isin(other_muts_rev).sum() & other_muts_rev.isin(dr_muts_rev).sum() > 0:
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print('\nAmbiguous muts corrected. Proceeding with downstream analysis')
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else:
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print('\nAmbiguous muts corrected. Quitting!')
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print('\nAmbiguous muts NOT corrected. Quitting!')
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sys.exit()
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#%% OUTFILE 3, write file: ambiguous muts and ambiguous mut counts
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@ -1543,8 +1553,12 @@ gene_LF2['index_orig'] = gene_LF2.index # need it for setting back later
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#%% FIXME: Add sanity check
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#gene_LF2['index_orig'].equals(gene_LF2.index)
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#%% Set index: 'mutationinformation' for adding multimode
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gene_LF3 = gene_LF2.set_index(['mutationinformation'])
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gene_LF2['Mut'] = gene_LF2['mutationinformation']
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#%% Further mappings: gene_LF3
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gene_LF3 = gene_LF2.set_index(['Mut'])
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gene_LF3.index
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#gene_LF3 = gene_LF2.set_index(['mutationinformation'])
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gene_LF3['dst_multimode'].value_counts()
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gene_LF3['dst_multimode'].value_counts().sum()
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#%% Multimode: dst
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@ -1640,6 +1654,15 @@ gene_LF3['mutation_info_labels_orig'].value_counts().sum()
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gene_LF3['mutation_info_labels'].value_counts()
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gene_LF3['mutation_info_labels'].value_counts().sum()
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gene_LF3['mutation_info_labels'].value_counts()
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gene_LF3['mutation_info'].value_counts()
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gene_LF3['mutation_info_orig'].value_counts()
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gene_LF3['mutation_info_orig'].value_counts().sum()
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gene_LF3['mutation_info_v1'].value_counts()
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gene_LF3['mutation_info_v1'].value_counts().sum()
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#%% TEST muts
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test_muts = ['G132A', 'V180F', 'G108R', 'A102P']
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test_muts = ['L4S', 'L4W', 'A102P']
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@ -1694,17 +1717,8 @@ foo_copy.loc[foo2.index, 'lineage_ucount'] = foo2['lineage_corrupt_ucount']
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#--------------------------
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# lineage multimode mode
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#--------------------------
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lineage_label_map = {'lineage1' : 'L1'
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, 'lineage2' : 'L2'
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, 'lineage3' : 'L3'
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, 'lineage4' : 'L4'
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, 'lineage5' : 'L5'
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, 'lineage6' : 'L6'
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, 'lineage7' : 'L7'
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, 'lineageBOV' : 'LBOV'}
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foo['lineage'].value_counts()
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foo_updated = foo.replace(to_replace ='lineage', value = 'L', regex = True) # works
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foo['lineage_labels'] = foo['lineage_labels'].str.replace('lineage', 'L')
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# foo_updated = foo.replace(to_replace ='lineage', value = 'L', regex = True) # doesn't specify a column
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foo['lineage_labels'] = foo['lineage']
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#df['team'] = df['team'].apply(lambda x: re.sub(r'[\n\r]*','', str(x)))
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@ -1727,8 +1741,8 @@ foo2['lineage_numeric'].value_counts()
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foo2['lineage_numeric_list'] = foo2['mutationinformation'].map(foo2.groupby('mutationinformation')['lineage_numeric'].apply(list))
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foo2['lineage_numeric_list']
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foo2['lineage_multimode'] = foo2.groupby(['mutationinformation'])['lineage_numeric'].agg(multimode)
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c2 = foo2[foo2.loc[:, 'MUT'].isin(['A102P'])]
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c2['lineage_numeric'].value_counts()
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@ -1743,36 +1757,160 @@ gene_LF3['lineage'].value_counts()
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# Create a column: lineage_corrupt
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gene_LF3['lineage_corrupt'] = gene_LF3['lineage']
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##############################
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# CHECK may be you only need it for multimode merge
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# set index
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# gene_LF3['index_orig_copy'] = gene_LF3['index_orig']
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# gene_LF3['index_orig_copy'].head
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# gene_LF3.index
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# gene_LF3 = gene_LF3.set_index(['index_orig_copy'])
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# gene_LF3.index
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################################
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# Create df with tidy_split: lineage
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lf_lin_split = tidy_split(gene_LF3, 'lineage_corrupt', sep = ';')
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lf_lin_split['lineage_corrupt'] = lf_lin_split['lineage_corrupt'].str.strip()
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# Add all lineages for each mutation
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lf_lin_split['lineage_corrupt_list'] = lf_lin_split['mutationinformation'].map(lf_lin_split.groupby('mutationinformation')['lineage_corrupt'].apply(list))
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# Add lineage unique count
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lf_lin_split['lineage_corrupt_ucount'] = lf_lin_split['mutationinformation'].map(lf_lin_split.groupby('mutationinformation')['lineage_corrupt'].nunique())
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#----------------------------------
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# Add lineage_set
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lf_lin_split['lineage_set'] = lf_lin_split['lineage_corrupt_list'].apply(lambda x : set(list(x)))
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lf_lin_split['lineage_ulist'] = lf_lin_split['lineage_set'].apply(lambda x : list(x))
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#--------------
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# Multimode lineage
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# ONLY after split else the corrupt ones don't get mapped
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#--------------
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# Do this mapping after tidy split else the ones with the
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lineage_label_numeric = {'L1' : 1
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, 'L2' : 2
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, 'L3' : 3
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, 'L4' : 4
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, 'L5' : 5
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, 'L6' : 6
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, 'L7' : 7
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, 'LBOV' : 8}
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# lineage_numeric = {'lineage1' : 1
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# , 'lineage2' : 2
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# , 'lineage3' : 3
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# , 'lineage4' : 4
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# , 'lineage5' : 5
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# , 'lineage6' : 6
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# , 'lineage7' : 7
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# , 'lineageBOV' : 8}
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lf_lin_split['lineage_corrupt'].value_counts()
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lf_lin_split['lineage_numeric'] = lf_lin_split['lineage_corrupt'].map(lineage_label_numeric)
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lf_lin_split['lineage_corrupt'].value_counts()
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lf_lin_split['lineage_numeric'].value_counts()
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lf_lin_split['lineage_numeric_list'] = lf_lin_split['mutationinformation'].map(lf_lin_split.groupby('mutationinformation')['lineage_numeric'].apply(list))
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lf_lin_split['lineage_numeric_list']
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#-------------------
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# change indices
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# to Mut as Multimode allows direct mapping this way!
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#-------------------
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lf_lin_split['Mut'] = lf_lin_split['mutationinformation']
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lf_lin_split['Mut']
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lf_lin_split = lf_lin_split.set_index(['Mut'])
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lf_lin_split.index
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lf_lin_split['lineage_multimode'] = lf_lin_split.groupby(['mutationinformation'])['lineage_numeric'].agg(multimode)
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lf_lin_split['lineage_multimode'].value_counts()
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#-------------------
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# Reset indices
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# to index orig to allow merge with gene_LF3
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#-------------------
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lf_lin_split.index
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lf_lin_split['index_orig_copy'] = lf_lin_split['index_orig']
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lf_lin_split = lf_lin_split.set_index(['index_orig_copy'])
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lf_lin_split.index
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###############################################################################
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#================================
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# Merge with gene_LF3 with
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# lf_lin_split
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#-----------------------------------
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#================================
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# set index
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gene_LF3['index_orig_copy'] = gene_LF3['index_orig']
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gene_LF3['index_orig_copy'].head
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gene_LF3.index
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gene_LF3 = gene_LF3.set_index(['index_orig_copy'])
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gene_LF3.index
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#-------------------------
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# colum lineage_ucount:
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# contribution of each distinct lineage
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#-------------------------
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gene_LF3['lineage_ucount'] = gene_LF3['lineage']
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# quick checks
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gene_LF3['lineage_ucount'].equals(gene_LF3['lineage'])
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#-------------------------
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# colum lineage list:
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#-------------------------
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#gene_LF3['lineage_set'] = gene_LF3['lineage']
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gene_LF3['lineage_ulist'] = gene_LF3['lineage']
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gene_LF3['lineage_list'] = gene_LF3['lineage']
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#-------------------------
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# colum lineage_list mode:
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#-------------------------
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gene_LF3['lineage_mode'] = gene_LF3['lineage']
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########################
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# merge based on indices
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gene_LF3.index.nunique()
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lf_lin_split.index.nunique()
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all(gene_LF3.index.isin(lf_lin_split.index))
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all(lf_lin_split.index.isin(gene_LF3.index))
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gene_LF3.index
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lf_lin_split.index
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if (gene_LF3.index.nunique() == lf_lin_split.index.nunique()) and ( all(gene_LF3.index.isin(lf_lin_split.index)) == all(lf_lin_split.index.isin(gene_LF3.index)) ):
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print('\nPass: merging lineage_ucount with gene_LF3')
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else:
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print('\nFail: Indices mismatch, cannot merge! Quitting!')
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sys.exit()
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###########################
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# magic merge happens here
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###########################
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gene_LF3.loc[lf_lin_split.index, 'lineage_ucount'] = lf_lin_split['lineage_corrupt_ucount']
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gene_LF3['lineage_ucount'].value_counts()
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#gene_LF3.loc[lf_lin_split.index, 'lineage_set'] = lf_lin_split['lineage_set']
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#gene_LF3['lineage_set'].value_counts()
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gene_LF3.loc[lf_lin_split.index, 'lineage_ulist'] = lf_lin_split['lineage_ulist']
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gene_LF3['lineage_ulist'].value_counts()
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gene_LF3.loc[lf_lin_split.index, 'lineage_list'] = lf_lin_split['lineage_corrupt_list']
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gene_LF3['lineage_list'].value_counts()
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gene_LF3.loc[lf_lin_split.index, 'lineage_mode'] = lf_lin_split['lineage_multimode']
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gene_LF3['lineage_mode'].value_counts()
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foo = gene_LF3[['mutationinformation', 'lineage', 'lineage_ucount'
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#, 'lineage_set'
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, 'lineage_ulist'
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, 'lineage_mode'
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, 'lineage_list']]
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#%% sanity checks
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check1 = gene_LF3[['mutationinformation', 'lineage', 'lineage_ucount']]
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check2 = check1[check1.loc[:, 'mutationinformation'].isin(['H57D'])]
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check2.value_counts()
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#%% Reset index: original indices [WAS above section Revised counts]
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#%% Reset index: original indices [WAS above ]
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#gene_LF3 = gene_LF3.reset_index()
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gene_LF3.index
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gene_LF3['mutationinformation'] = gene_LF3.index
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@ -1780,5 +1918,14 @@ gene_LF3 = gene_LF3.set_index(['index_orig'])
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gene_LF3[['mutationinformation']]
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gene_LF3.index
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#%% Remove MUT column not needed
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# sanity check
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if (all(gene_LF3['Mut'] == gene_LF3['mutationinformation'])):
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print('\nPass: Mutationinformation check successful')
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else:
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sys.exit('\nERROR: mutationin cross checks failed. Please check your group_by() aggregate functions')
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# Drop mutation column
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gene_LF3.drop(['MUT'], axis = 1, inplace = True)
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#%% ADD summary results
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#%% final output file with selected columns
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