Mercurial > repos > ieguinoa > ena_upload
comparison extract_tables.py @ 0:5d59238cd3f4 draft
Uploaded
author | ieguinoa |
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date | Wed, 02 Feb 2022 17:16:15 +0000 |
parents | |
children | 2f7a70c0d3ab |
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-1:000000000000 | 0:5d59238cd3f4 |
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1 import argparse | |
2 import json | |
3 import pathlib | |
4 from datetime import datetime | |
5 | |
6 """ | |
7 Parse the configfile generated by the Galaxy tool. | |
8 This file is JSON-formatted and should be converted to a set of tabular files. | |
9 """ | |
10 | |
11 FILE_FORMAT = 'fastq' | |
12 | |
13 parser = argparse.ArgumentParser() | |
14 parser.add_argument('--studies', dest='studies_json_path', required=True) | |
15 parser.add_argument('--out_dir', dest='out_path', required=True) | |
16 parser.add_argument('--action', dest='action', required=True) | |
17 args = parser.parse_args() | |
18 | |
19 with open(args.studies_json_path, 'r') as studies_json_file: | |
20 studies_dict = json.load(studies_json_file) | |
21 studies_table = open(pathlib.Path(args.out_path) / 'studies.tsv', 'w') | |
22 studies_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'study_type', | |
23 'study_abstract', 'pubmed_id', 'submission_date']) + '\n') | |
24 samples_table = open(pathlib.Path(args.out_path) / 'samples.tsv', 'w') | |
25 experiments_table = open(pathlib.Path(args.out_path) / 'experiments.tsv', 'w') | |
26 experiments_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'study_alias', | |
27 'sample_alias', 'design_description', 'library_name', | |
28 'library_strategy', 'library_source', 'library_selection', | |
29 'library_layout', 'insert_size', | |
30 'library_construction_protocol', 'platform', 'instrument_model', | |
31 'submission_date']) + '\n') | |
32 runs_table = open(pathlib.Path(args.out_path) / 'runs.tsv', 'w') | |
33 runs_table.write('\t'.join(['alias', 'status', 'accession', 'experiment_alias', 'file_name', | |
34 'file_format', 'file_checksum', 'submission_date']) + '\n') | |
35 | |
36 action = args.action | |
37 | |
38 dt_oobj = datetime.now(tz=None) | |
39 timestamp = dt_oobj.strftime("%Y%m%d_%H:%M:%S") | |
40 for study_index, study in enumerate(studies_dict): | |
41 study_alias = 'study_' + str(study_index) + '_' + timestamp | |
42 studies_table.write('\t'.join([study_alias, action, 'ENA_accession', study['title'], | |
43 study['type'], study['abstract'], study['pubmed_id'], | |
44 'ENA_submission_data'])) | |
45 if "geo_location" in study['samples'][0].keys(): # sample belongs to a viral sample | |
46 samples_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'scientific_name', | |
47 'taxon_id', 'sample_description', 'collection_date', | |
48 'geographic_location', 'host_common_name', 'host_subject_id', | |
49 'host_health_state', 'host_sex', 'host_scientific_name', | |
50 'collector_name', 'collecting_institution', 'isolate', | |
51 'submission_date']) + '\n') | |
52 else: | |
53 samples_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'scientific_name', | |
54 'taxon_id', 'sample_description', 'submission_date']) + '\n') | |
55 for sample_index, sample in enumerate(study['samples']): | |
56 sample_alias = 'sample_' + str(sample_index) + '_' + timestamp | |
57 if "geo_location" in sample.keys(): # sample belongs to a viral sample | |
58 if sample['collector_name'] == '': | |
59 sample['collector_name'] = 'unknown' | |
60 samples_table.write('\t'.join([sample_alias, action, 'ena_accession', sample['title'], | |
61 sample['tax_name'], sample['tax_id'], | |
62 sample['description'], sample['collection_date'], | |
63 sample['geo_location'], sample['host_common_name'], | |
64 sample['host_subject_id'], sample['host_health_state'], | |
65 sample['host_sex'], sample['host_scientific_name'], | |
66 sample['collector_name'], | |
67 sample['collecting_institution'], sample['isolate'], | |
68 'ENA_submission_date']) + '\n') | |
69 else: | |
70 samples_table.write('\t'.join([sample_alias, action, 'ena_accession', sample['title'], | |
71 sample['tax_name'], sample['tax_id'], | |
72 sample['description'], 'ENA_submission_date']) + '\n') | |
73 for exp_index, exp in enumerate(sample['experiments']): | |
74 exp_alias = 'experiment_' + str(exp_index) + '.' + str(sample_index) + '_' + timestamp | |
75 lib_alias = 'library_' + str(exp_index) + '_' + str(sample_index) | |
76 experiments_table.write('\t'.join([exp_alias, action, 'accession_ena', exp['title'], | |
77 study_alias, sample_alias, exp['experiment_design'], | |
78 lib_alias, exp['library_strategy'], | |
79 exp['library_source'], exp['library_selection'], | |
80 exp['library_layout'].lower(), exp['insert_size'], | |
81 exp['library_construction_protocol'], | |
82 exp['platform'], exp['instrument_model'], | |
83 'submission_date_ENA']) + '\n') | |
84 run_index = 0 | |
85 # exp['runs'] is a list of lists | |
86 for (base_run, run_files) in exp['runs']: | |
87 run_index += 1 | |
88 if base_run != '': | |
89 run_alias = base_run | |
90 else: | |
91 # no alias provided, generated a unique one | |
92 run_alias = '_'.join(['run_' + str(run_index), str(exp_index), | |
93 str(sample_index)]) + '_' + timestamp | |
94 for file_entry in run_files: | |
95 runs_table.write('\t'.join([run_alias, action, 'ena_run_accession', exp_alias, | |
96 file_entry, FILE_FORMAT, 'file_checksum', | |
97 'submission_date_ENA']) + '\n') | |
98 | |
99 studies_table.close() | |
100 samples_table.close() | |
101 experiments_table.close() | |
102 runs_table.close() |