| import json |
| import pandas as pd |
| import os |
|
|
| AAs = set('ACDEFGHIKLMNPQRSTVWY') |
|
|
| seqs_abs = { |
| 'cr6261_vh': 'EVQLVESGAEVKKPGSSVKVSCKASGGPFRSYAISWVRQAPGQGPEWMGGIIPIFGTTKYAPKFQGRVTITADDFAGTVYMELSSLRSEDTAMYYCAKHMGYQVRETMDVWGKGTTVTVSS', |
| 'cr9114_vh': 'QVQLVQSGAEVKKPGSSVKVSCKSSGGTSNNYAISWVRQAPGQGLDWMGGISPIFGSTAYAQKFQGRVTISADIFSNTAYMELNSLTSEDTAVYFCARHGNYYYYSGMDVWGQGTTVTVSS', |
| 'g6_vh': 'EVQLVESGGGLVQPGGSLRLSCAASGFTISDYWIHWVRQAPGKGLEWVAGITPAGGYTYYADSVKGRFTISADTSKNTAYLQMNSLRAEDTAVYYCARFVFFLPYAMDYWGQGTLVTV', |
| 'g6_vl': 'DIQMTQSPSSLSASVGDRVTITCRASQDVSTAVAWYQQKPGKAPKLLIYSASFLYSGVPSRFSGSGSGTDFTLTISSLQPEDFATYYCQQSYTTPPTFGQGTKVEIK', |
| 'beb_vh': 'QITLKESGPTLVKPTQTLTLTCTFSGFSLSISGVGVGWLRQPPGKALEWLALIYWDDDKRYSPSLKSRLTISKDTSKNQVVLKMTNIDPVDTATYYCAHHSISTIFDHWGQGTLVTVSS', |
| 'beb_vl' : 'QSALTQPASVSGSPGQSITISCTATSSDVGDYNYVSWYQQHPGKAPKLMIFEVSDRPSGISNRFSGSKSGNTASLTISGLQAEDEADYYCSSYTTSSAVFGGGTKLTVL', |
| 'sa58_vh': 'QVQLAQSGSELRKPGASVKVSCDTSGHSFTSNAIHWVRQAPGQGLEWMGWINTDTGTPTYAQGFTGRFVFSLDTSARTAYLQISSLKADDTAVFYCARERDYSDYFFDYWGQGTLVTVSS', |
| 'sa58_vl': 'EVVMTQSPASLSVSPGERATLSCRARASLGISTDLAWYQQRPGQAPRLLIYGASTRATGIPARFSGSGSGTEFTLTISSLQSEDSAVYYCQQYSNWPLTFGGGTKVEIK', |
| } |
|
|
|
|
| def parse_abysis(seq, seq_name): |
| fname = f'data/abysis/abysis_counts_{seq_name}.json' |
| with open(fname) as f: |
| json_data = json.load(f) |
|
|
| data = [] |
| for idx, freq_table in enumerate(json_data['frequencies']): |
| wt = seq[idx] |
| total = freq_table['total'] |
| for entry in freq_table['counts']: |
| if entry['aa'] == seq[idx]: |
| wt_frac = entry['c'] / total |
| aa_to_freq, seen = {}, set() |
| for entry in freq_table['counts']: |
| mt = entry['aa'] |
| seen.add(mt) |
| counts = entry['c'] |
| frac = entry['c'] / total |
| ratio = frac / wt_frac |
| data.append([ idx + 1, wt, mt, counts, frac, ratio ]) |
| for mt in AAs - seen: |
| data.append([ idx + 1, wt, mt, 0, 0., 0. ]) |
|
|
| df = pd.DataFrame(data, columns=[ |
| 'pos', |
| 'wt', |
| 'mt', |
| 'counts', |
| 'fraction', |
| 'likelihood_ratio', |
| ]) |
|
|
| if any(prefix in seq_name for prefix in ['cr6261', 'cr9114', 'g6']): |
| subdirectory = seq_name.split('_')[0] |
| else: |
| subdirectory = '' |
|
|
| output_dir = os.path.join('output', 'ab_mutagenesis_expts', subdirectory) |
| os.makedirs(output_dir, exist_ok=True) |
|
|
| output_path = os.path.join(output_dir, f'abysis_counts_{seq_name}.txt') |
| df.to_csv(output_path, sep='\t') |
|
|
| if __name__ == '__main__': |
| for seq_name in seqs_abs: |
| seq = seqs_abs[seq_name] |
| parse_abysis(seq, seq_name) |
