resolving missing mutation info in combining script
This commit is contained in:
parent
bba3487829
commit
ddefcd7841
3 changed files with 87 additions and 17 deletions
|
|
@ -54,6 +54,7 @@ os.getcwd()
|
|||
# FIXME: local imports
|
||||
#from combining import combine_dfs_with_checks
|
||||
from combining_FIXME import detect_common_cols
|
||||
from reference_dict import oneletter_aa_dict # CHECK DIR STRUC THERE!
|
||||
#=======================================================================
|
||||
#%% command line args
|
||||
arg_parser = argparse.ArgumentParser()
|
||||
|
|
@ -155,6 +156,8 @@ ncols_m1 = len(mcsm_foldx_dfs.columns)
|
|||
|
||||
print('\n\nResult of first merge:', mcsm_foldx_dfs.shape
|
||||
, '\n===================================================================')
|
||||
mcsm_foldx_dfs[merging_cols_m1].apply(len)
|
||||
mcsm_foldx_dfs[merging_cols_m1].apply(len) == len(mcsm_foldx_dfs)
|
||||
#%%============================================================================
|
||||
print('==================================='
|
||||
, '\nSecond merge: dssp + kd'
|
||||
|
|
@ -183,6 +186,8 @@ ncols_m3 = len(dssp_kd_rd_dfs.columns)
|
|||
|
||||
print('\n\nResult of Third merge:', dssp_kd_rd_dfs.shape
|
||||
, '\n===================================================================')
|
||||
dssp_kd_rd_dfs[merging_cols_m3].apply(len)
|
||||
dssp_kd_rd_dfs[merging_cols_m3].apply(len) == len(dssp_kd_rd_dfs)
|
||||
#%%============================================================================
|
||||
print('======================================='
|
||||
, '\nFourth merge: First merge + Third merge'
|
||||
|
|
@ -203,12 +208,14 @@ else:
|
|||
|
||||
print('\nResult of Fourth merge:', combined_df.shape
|
||||
, '\n===================================================================')
|
||||
combined_df[merging_cols_m4].apply(len)
|
||||
combined_df[merging_cols_m4].apply(len) == len(combined_df)
|
||||
#%%============================================================================
|
||||
|
||||
# OR merges: TEDIOUSSSS!!!!
|
||||
|
||||
|
||||
#%%RRRR
|
||||
#%%
|
||||
print('==================================='
|
||||
, '\nFifth merge: afor_df + afor_kin_df'
|
||||
, '\n===================================')
|
||||
|
|
@ -220,8 +227,6 @@ afor_df = pd.read_csv(infile_afor, sep = ',')
|
|||
afor_kin_df = pd.read_csv(infile_afor_kin, sep = ',')
|
||||
afor_kin_df.columns = afor_kin_df.columns.str.lower()
|
||||
|
||||
|
||||
|
||||
merging_cols_m5 = detect_common_cols(afor_df, afor_kin_df)
|
||||
|
||||
print('Dim of afor_df:', afor_df.shape
|
||||
|
|
@ -244,7 +249,7 @@ common_muts = len(afor_df[afor_df['mutation'].isin(afor_kin_df['mutation'])])
|
|||
extra_muts_myor = afor_kin_df.shape[0] - common_muts
|
||||
|
||||
print('=========================================='
|
||||
, '\nmy or calcs', extra_muts_myor, 'extra mutation\n'
|
||||
, '\nmy or calcs has', extra_muts_myor, 'extra mutations'
|
||||
, '\n==========================================')
|
||||
|
||||
print('Expected cals for merging with outer_join...')
|
||||
|
|
@ -261,12 +266,13 @@ else:
|
|||
, '\nCheck expected rows and cols calculation and join type')
|
||||
|
||||
print('Dim of merged ors_df:', ors_df.shape)
|
||||
|
||||
ors_df[merging_cols_m5].apply(len)
|
||||
ors_df[merging_cols_m5].apply(len) == len(ors_df)
|
||||
#%%============================================================================
|
||||
# formatting ors_df
|
||||
|
||||
ors_df.columns
|
||||
|
||||
|
||||
# Dropping unncessary columns: already removed in ealier preprocessing
|
||||
#cols_to_drop = ['reference_allele', 'alternate_allele', 'symbol' ]
|
||||
cols_to_drop = ['n_miss']
|
||||
|
|
@ -324,7 +330,7 @@ column_order = ['mutation'
|
|||
#, 'n_miss'
|
||||
]
|
||||
|
||||
if ( (len(column_order) == ors_df.shape[1]) and (DataFrame(column_order).isin(ors_df.columns).all().all()):
|
||||
if ( (len(column_order) == ors_df.shape[1]) and (DataFrame(column_order).isin(ors_df.columns).all().all())):
|
||||
print('PASS: Column order generated for all:', len(column_order), 'columns'
|
||||
, '\nColumn names match, safe to reorder columns'
|
||||
, '\nApplying column order to df...' )
|
||||
|
|
@ -357,10 +363,35 @@ print('Checking mutations in the two dfs:'
|
|||
|
||||
#print('\nNo. of common muts:', np.intersect1d(combined_df['mutationinformation'], ors_df_ordered['mutationinformation']) )
|
||||
|
||||
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
|
||||
combined_df_all = pd.merge(combined_df, ors_df, on = merging_cols_m6, how = l_join)
|
||||
combined_df_all.shape
|
||||
|
||||
# populate mut_info_f1
|
||||
combined_df_all['mut_info_f1'].isna().sum()
|
||||
combined_df_all['mut_info_f1'] = combined_df_all['position'].astype(str) + combined_df_all['wild_type'] + '>' + combined_df_all['position'].astype(str) + combined_df_all['mutant_type']
|
||||
combined_df_all['mut_info_f1'].isna().sum()
|
||||
|
||||
# populate mut_type
|
||||
combined_df_all['mut_type'].isna().sum()
|
||||
#mut_type_word = combined_df_all['mut_type'].value_counts()
|
||||
mut_type_word = 'missense' # FIXME, should be derived
|
||||
combined_df_all['mut_type'].fillna(mut_type_word, inplace = True)
|
||||
combined_df_all['mut_type'].isna().sum()
|
||||
|
||||
# populate gene_id
|
||||
combined_df_all['gene_id'].isna().sum()
|
||||
#gene_id_word = combined_df_all['gene_id'].value_counts()
|
||||
gene_id_word = 'Rv2043c' # FIXME, should be derived
|
||||
combined_df_all['gene_id'].fillna(gene_id_word, inplace = True)
|
||||
combined_df_all['gene_id'].isna().sum()
|
||||
|
||||
# populate gene_name
|
||||
combined_df_all['gene_name'].isna().sum()
|
||||
combined_df_all['gene_name'].value_counts()
|
||||
combined_df_all['gene_name'].fillna(gene, inplace = True)
|
||||
combined_df_all['gene_name'].isna().sum()
|
||||
|
||||
|
||||
# FIXME: DIM
|
||||
# only with left join!
|
||||
outdf_expected_rows = len(combined_df)
|
||||
|
|
@ -383,11 +414,52 @@ else:
|
|||
, '\nmuts in df2 but NOT in df1:'
|
||||
, ors_df['mutationinformation'].isin(combined_df['mutationinformation']).sum())
|
||||
sys.exit()
|
||||
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
|
||||
# nan in mutation col
|
||||
# FIXME: should get fixmed with JP's resolved dataset!?
|
||||
combined_df_all['mutation'].isna().sum()
|
||||
baz = combined_df_all[combined_df_all['mutation'].isna()]
|
||||
|
||||
|
||||
#%% IMPORTANT: check if mutation related info is all populated after this merge
|
||||
# FIXME: should get fixed with JP's resolved dataset!?
|
||||
check_nan = combined_df_all.isna().sum(axis = 0)
|
||||
# relevant mut cols
|
||||
check_mut_cols = merging_cols_m5 + merging_cols_m6
|
||||
|
||||
count_na_mut_cols = combined_df_all[check_mut_cols].isna().sum().reset_index().rename(columns = {'index': 'col_name', 0: 'na_count'})
|
||||
|
||||
if (count_na_mut_cols['na_count'].sum() > 0).any():
|
||||
# FIXME: static override, generate 'mutation' from variable
|
||||
na_muts_n = combined_df_all['mutation'].isna().sum()
|
||||
baz = combined_df_all[combined_df_all['mutation'].isna()]
|
||||
baz = baz[check_mut_cols]
|
||||
print(na_muts_n, 'mutations have missing \'mutation\' info.'
|
||||
, '\nFetching these from reference dict...')
|
||||
|
||||
lookup_dict = dict()
|
||||
for k, v in oneletter_aa_dict.items():
|
||||
lookup_dict[k] = v['three_letter_code_lower']
|
||||
print(lookup_dict)
|
||||
wt_3let = combined_df_all['wild_type'].map(lookup_dict).str.capitalize()
|
||||
#print(wt_3let)
|
||||
pos = combined_df_all['position'].astype(str)
|
||||
#print(pos)
|
||||
mt_3let = combined_df_all['mutant_type'].map(lookup_dict).str.capitalize()
|
||||
#print(mt_3let)
|
||||
baz['mutation'] = 'pnca_p.' + wt_3let + pos + mt_3let
|
||||
print(combined_df_all['mutation'])
|
||||
|
||||
# populate mut_info_f2
|
||||
combined_df_all['mut_info_f2'] = combined_df_all['mutation'].str.replace(gene_match.lower(), 'p.', regex = True)
|
||||
|
||||
#%% merge
|
||||
#merging_cols_m7 = detect_common_cols(combined_df_all, baz)
|
||||
|
||||
baz2 = baz[['mutationinformation', 'mut_info_f2']]
|
||||
baz2 = baz2.drop_duplicates()
|
||||
merging_cols_m7 = detect_common_cols(combined_df_all, baz2)
|
||||
|
||||
combined_df_all2 = pd.merge(combined_df_all, baz2
|
||||
#, on = merging_cols_m7
|
||||
, on = 'mutationinformation'
|
||||
, how = o_join)
|
||||
|
||||
#%%============================================================================
|
||||
output_cols = combined_df_all.columns
|
||||
print('Output cols:', output_cols)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue