Mercurial > repos > iuc > ena_upload

comparison process_xlsx.py @ 0:382518f24d6d draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ena_upload commit 57b434bcf493554d060a99b65e66f274d5c00e0a"
author iuc
date Sat, 28 Nov 2020 09:45:44 +0000
parents
children 57251c760cab
comparison
equal deleted inserted replaced
-1:000000000000 0:382518f24d6d
1 import argparse
2 import pathlib
3 import sys
4
5 import xlrd
6
7
8 FILE_FORMAT = 'fastq'
9
10
11 def extract_data(xl_sheet, expected_columns):
12 """
13 1. Check that the columns I expect are present in the sheet
14 (any order and mixed with others, it's just a verification that
15 the user filled the correct template)
16 2. Fill a dictionary with the rows data indexed by first column in list"""
17 sheet_columns = {}
18 for sh_col in range(xl_sheet.ncols):
19 if xl_sheet.cell(0, sh_col).value in expected_columns:
20 if xl_sheet.cell(0, sh_col).value in sheet_columns.keys():
21 sys.exit("Duplicated columns")
22 else:
23 sheet_columns[xl_sheet.cell(0, sh_col).value] = sh_col
24 for col in range(len(expected_columns)):
25 assert expected_columns[col] in sheet_columns.keys(), \
26 "Expected column %s not found" % expected_columns[col]
27
28 # fetch rows in a dict
29 data_dict = {}
30 # the first of the expected columns will be the index
31 index_col = sheet_columns[expected_columns[0]]
32 # skip first 2 rows: column names + comments rows
33 for row_id in range(2, xl_sheet.nrows):
34 row_dict = {}
35 for col in range(1, len(expected_columns)):
36 sheet_col_index = sheet_columns[expected_columns[col]]
37 row_dict[expected_columns[col]] = xl_sheet.cell(row_id, sheet_col_index).value
38 # should check for duplicate alias/ids?
39 data_dict[xl_sheet.cell(row_id, index_col).value] = row_dict
40 return data_dict
41
42
43 parser = argparse.ArgumentParser()
44 parser.add_argument('--form', dest='xlsx_path', required=True)
45 parser.add_argument('--out_dir', dest='out_path', required=True)
46 parser.add_argument('--action', dest='action', required=True)
47 parser.add_argument('--vir', dest='viral_submission', required=False, action='store_true')
48 args = parser.parse_args()
49
50 xl_workbook = xlrd.open_workbook(args.xlsx_path)
51
52 # PARSE STUDIES
53 #################
54 xl_sheet = xl_workbook.sheet_by_name('ENA_study')
55 if xl_sheet.nrows < 3:
56 raise ValueError('No entries found in studies sheet')
57 studies_dict = {}
58 studies_col = ['alias', 'title', 'study_type', 'study_abstract']
59 studies_dict = extract_data(xl_sheet, studies_col)
60
61 # PARSE SAMPLES
62 #################
63 xl_sheet = xl_workbook.sheet_by_name('ENA_sample')
64 if xl_sheet.nrows < 3:
65 raise ValueError('No entries found in samples')
66 if args.viral_submission:
67 samples_cols = ['alias', 'title', 'scientific_name', 'sample_description',
68 'geographic location (country and/or sea)', 'host common name',
69 'host health state', 'host sex', 'host scientific name', 'collector name',
70 'collection date', 'collecting institution', 'isolate']
71 else:
72 samples_cols = ['alias', 'title', 'scientific_name', 'sample_description']
73 samples_dict = extract_data(xl_sheet, samples_cols)
74
75 # PARSE EXPERIMENTS
76 #################
77 xl_sheet = xl_workbook.sheet_by_name('ENA_experiment')
78 if xl_sheet.nrows < 3:
79 raise ValueError('No experiments found in experiments sheet')
80 exp_columns = ['alias', 'title', 'study_alias', 'sample_alias', 'design_description', 'library_name',
81 'library_strategy', 'library_source', 'library_selection', 'library_layout',
82 'insert_size', 'library_construction_protocol', 'platform', 'instrument_model']
83 experiments_dict = extract_data(xl_sheet, exp_columns)
84
85 # PARSE RUNS SHEET
86 #################
87 xl_sheet = xl_workbook.sheet_by_name('ENA_run')
88 if xl_sheet.nrows < 3:
89 raise ValueError('No entries found in runs sheet')
90 run_cols = ['alias', 'experiment_alias', 'file_name', 'file_format']
91 runs_dict = extract_data(xl_sheet, run_cols)
92
93 # WRITE HEADERS TO TABLES
94 studies_table = open(pathlib.Path(args.out_path) / 'studies.tsv', 'w')
95 studies_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'study_type',
96 'study_abstract', 'pubmed_id', 'submission_date']) + '\n')
97 samples_table = open(pathlib.Path(args.out_path) / 'samples.tsv', 'w')
98 if args.viral_submission:
99 samples_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'scientific_name',
100 'taxon_id', 'sample_description', 'collection_date',
101 'geographic_location', 'host_common_name', 'host_subject_id',
102 'host_health_state', 'host_sex', 'host_scientific_name',
103 'collector_name', 'collecting_institution', 'isolate',
104 'submission_date']) + '\n')
105 else:
106 samples_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'scientific_name',
107 'taxon_id', 'sample_description', 'submission_date']) + '\n')
108
109 experiments_table = open(pathlib.Path(args.out_path) / 'experiments.tsv', 'w')
110 experiments_table.write('\t'.join(['alias', 'status', 'accession', 'title', 'study_alias',
111 'sample_alias', 'design_description', 'library_name',
112 'library_strategy', 'library_source', 'library_selection',
113 'library_layout', 'insert_size', 'library_construction_protocol',
114 'platform', 'instrument_model', 'submission_date']) + '\n')
115
116 runs_table = open(pathlib.Path(args.out_path) / 'runs.tsv', 'w')
117 runs_table.write('\t'.join(['alias', 'status', 'accession', 'experiment_alias', 'file_name',
118 'file_format', 'file_checksum', 'submission_date']) + '\n')
119 action = args.action
120
121 # WRITE DICTIONARIES TO TABLE FILES
122
123 # ADD A TIMESTAMP TO THE ALIAS? SEEMS LIKE ENA REQUIRES ALL ENTRIES FOR A WEBIN TO HAVE UNIQUE IDS?
124 # dt_oobj = datetime.now(tz=None)
125 # timestamp = dt_oobj.strftime("%Y%m%d_%H:%M:%S")
126 for study_alias, study in studies_dict.items():
127 # study_alias = study_alias + '_' + timestamp
128 studies_table.write('\t'.join([study_alias, action, 'ENA_accession', study['title'],
129 study['study_type'], study['study_abstract'], '',
130 'ENA_submission_data']) + '\n') # assuming no pubmed_id
131 for sample_alias, sample in samples_dict.items():
132 # sample_alias = sample_alias + '_' + timestamp
133 if args.viral_submission:
134 if sample['collector name'] == '':
135 sample['collector name'] = 'unknown'
136 samples_table.write('\t'.join([sample_alias, action, 'ena_accession', sample['title'],
137 sample['scientific_name'], 'tax_id_updated_by_ENA',
138 sample['sample_description'], sample['collection date'],
139 sample['geographic location (country and/or sea)'],
140 sample['host common name'], 'host subject id',
141 sample['host health state'], sample['host sex'],
142 sample['host scientific name'], sample['collector name'],
143 sample['collecting institution'], sample['isolate'],
144 'ENA_submission_date']) + '\n')
145 else:
146 samples_table.write('\t'.join([sample_alias, action, 'ena_accession', sample['title'],
147 sample['scientific_name'], 'tax_id_updated_by_ENA',
148 sample['sample_description']]) + '\n')
149 for exp_alias, exp in experiments_dict.items():
150 # should I check here if any experiment has a study or sample alias that is incorrect?
151 # (not listed in the samples or study dict)
152 # process the experiments for this sample
153 if exp['sample_alias'] == sample_alias:
154 lib_alias = 'library_' + exp_alias + '_' + exp['sample_alias']
155 experiments_table.write('\t'.join([exp_alias, action, 'accession_ena', exp['title'],
156 exp['study_alias'], sample_alias,
157 exp['design_description'], lib_alias,
158 exp['library_strategy'], exp['library_source'],
159 exp['library_selection'],
160 exp['library_layout'].lower(),
161 str(int(exp['insert_size'])),
162 exp['library_construction_protocol'],
163 exp['platform'], exp['instrument_model'],
164 'submission_date_ENA']) + '\n')
165 for run_alias, run in runs_dict.items():
166 if run['experiment_alias'] == exp_alias:
167 runs_table.write('\t'.join([run_alias, action, 'ena_run_accession', exp_alias,
168 run['file_name'], FILE_FORMAT, 'file_checksum',
169 'submission_date_ENA']) + '\n')
170 studies_table.close()
171 samples_table.close()
172 experiments_table.close()
173 runs_table.close()