Mercurial > repos > kkonganti > cfsan_cronology

comparison 0.2.0/bin/index_pdg_metadata.py @ 11:a5f31c44f8c9

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload
author kkonganti
date Mon, 15 Jul 2024 16:11:44 -0400
parents
children
comparison
equal deleted inserted replaced
10:ddf7a172bf30 11:a5f31c44f8c9
1 #!/usr/bin/env python3
2
3 # Kranti Konganti
4
5 import argparse
6 import inspect
7 import logging
8 import os
9 import pickle
10 import pprint
11 import re
12 from collections import defaultdict
13
14
15 # Multiple inheritence for pretty printing of help text.
16 class MultiArgFormatClasses(argparse.RawTextHelpFormatter, argparse.ArgumentDefaultsHelpFormatter):
17 pass
18
19
20 # Main
21 def main() -> None:
22 """
23 This script works only in the context of `cronology_db` Nextflow workflow.
24 It takes an UNIX path to directory containing the following files:
25 1. PDG metadata file (Ex: `PDG000000043.204.metadata.tsv`)
26 2. PDG SNP Cluster metadata file (Ex: `PDG000000043.204.reference_target.cluster_list.tsv`)
27 3. A list of possibly downloadable assembly accessions (one per line) from the metadata file.
28 and then generates a pickled file with relevant metadata columns mentioned with the -cols option.
29 """
30
31 # Set logging.
32 logging.basicConfig(
33 format="\n" + "=" * 55 + "\n%(asctime)s - %(levelname)s\n" + "=" * 55 + "\n%(message)s\n\n",
34 level=logging.DEBUG,
35 )
36
37 # Debug print.
38 ppp = pprint.PrettyPrinter(width=55)
39 prog_name = os.path.basename(inspect.stack()[0].filename)
40
41 parser = argparse.ArgumentParser(
42 prog=prog_name, description=main.__doc__, formatter_class=MultiArgFormatClasses
43 )
44
45 required = parser.add_argument_group("required arguments")
46
47 required.add_argument(
48 "-pdg_dir",
49 dest="pdg_dir",
50 default=False,
51 required=True,
52 help="Absolute UNIX path to directory containing the following files.\nEx:"
53 + "\n1. PDG000000043.204.metadata.tsv"
54 + "\n2. PDG000000043.204.reference_target.cluster_list.tsv"
55 + "\n3. A file of assembly accessions, one per line parsed out from"
56 + "\n the metadata file.",
57 )
58 parser.add_argument(
59 "-mlst",
60 dest="mlst_results",
61 required=False,
62 help="Absolute UNIX path to MLST results file\nIf MLST results exists for a accession, they"
63 + "\nwill be included in the index.",
64 )
65 parser.add_argument(
66 "-pdg_meta_pat",
67 dest="pdg_meta_pat",
68 default="PDG\d+\.\d+\.metadata\.tsv",
69 required=False,
70 help="The pattern to be used to search for PDG metadata\nfile.",
71 )
72 parser.add_argument(
73 "-pdg_snp_meta_pat",
74 dest="pdg_snp_meta_pat",
75 default="PDG\d+\.\d+\.reference\_target\.cluster\_list\.tsv",
76 required=False,
77 help="The pattern to be used to search for PDG SNP Cluster metadata\nfile.",
78 )
79 parser.add_argument(
80 "-pdg_accs_filename_pat",
81 dest="pdg_accs_fn_pat",
82 default="accs_all.txt",
83 required=False,
84 help="The filename to look for where all the parsed GC[AF] accessions are stored,\n"
85 + "one per line.",
86 )
87 parser.add_argument(
88 "-cols",
89 dest="metadata_cols",
90 default="epi_type,collected_by,collection_date,host,"
91 + "\nhost_disease,isolation_source,outbreak,sample_name,scientific_name,serovar,"
92 + "\nsource_type,strain,computed_types,target_acc",
93 required=False,
94 help="The data in these metadata columns will be indexed for each\nisolate.",
95 )
96 parser.add_argument(
97 "-fs",
98 dest="force_write_pick",
99 action="store_true",
100 required=False,
101 help="By default, when -s flag is on, the pickle file named *.IDXD_PDG_METAD.pickle"
102 + "\nis written to CWD. If the file exists, the program will not overwrite"
103 + "\nand exit. Use -fs option to overwrite.",
104 )
105 parser.add_argument(
106 "-op",
107 dest="out_prefix",
108 default="IDXD_PDG_METAD",
109 help="Set the output file prefix for indexed PDG metadata.",
110 )
111 parser.add_argument(
112 "-pfs",
113 dest="pdg_meta_fs",
114 default="\t",
115 help="Change the field separator of the PDG metadata file.",
116 )
117
118 args = parser.parse_args()
119 pdg_dir = os.path.abspath(args.pdg_dir)
120 mcols = args.metadata_cols
121 f_write_pick = args.force_write_pick
122 out_prefix = args.out_prefix
123 pdg_meta_fs = args.pdg_meta_fs
124 mlst_res = args.mlst_results
125 acc_pat = re.compile(r"^GC[AF]\_\d+\.?\d*")
126 mcols_pat = re.compile(r"[\w+\,]")
127 pdg_meta_pat = re.compile(f"{args.pdg_meta_pat}")
128 pdg_snp_meta_pat = re.compile(f"{args.pdg_snp_meta_pat}")
129 pdg_accs_fn_pat = re.compile(f"{args.pdg_accs_fn_pat}")
130 target_acc_col = 41
131 acc_col = 9
132 num_accs_check = list()
133 mlst_sts = dict()
134 acceptable_num_mlst_cols = 10
135 mlst_st_col = 2
136 mlst_acc_col = 0
137
138 # Basic checks
139
140 if os.path.exists(pdg_dir) and os.path.isdir(pdg_dir):
141 pdg_meta_file = [f for f in os.listdir(pdg_dir) if pdg_meta_pat.match(f)]
142 pdg_snp_meta_file = [f for f in os.listdir(pdg_dir) if pdg_snp_meta_pat.match(f)]
143 pdg_acc_all = [f for f in os.listdir(pdg_dir) if pdg_accs_fn_pat.match(f)]
144 req_files = [len(pdg_meta_file), len(pdg_snp_meta_file), len(pdg_acc_all)]
145 if any(x > 1 for x in req_files):
146 logging.error(
147 f"Directory {os.path.basename(pdg_dir)} contains"
148 + "\ncontains mulitple files matching the search pattern."
149 )
150 exit(1)
151 elif any(x == 0 for x in req_files):
152 logging.error(
153 f"Directory {os.path.basename(pdg_dir)} does not contain"
154 + "\nany files matching the following file patterns:"
155 + f"\n{pdg_meta_pat.pattern}"
156 + f"\n{pdg_snp_meta_pat.pattern}"
157 + f"\n{pdg_accs_fn_pat.pattern}"
158 )
159 exit(1)
160 pdg_meta_file = os.path.join(pdg_dir, "".join(pdg_meta_file))
161 pdg_snp_meta_file = os.path.join(pdg_dir, "".join(pdg_snp_meta_file))
162 pdg_acc_all = os.path.join(pdg_dir, "".join(pdg_acc_all))
163 else:
164 logging.error(f"Directory path {pdg_dir} does not exist.")
165 exit(1)
166
167 if mlst_res and not (os.path.exists(mlst_res) or os.path.getsize(mlst_res) > 0):
168 logging.error(
169 f"Requested to index MLST results. but the file {os.path.basename(mlst_res)}"
170 + "does not exist or the file is empty."
171 )
172 exit(1)
173 elif mlst_res:
174 with open(mlst_res, "r") as mlst_res_fh:
175 header = mlst_res_fh.readline()
176 mlst_res_has_10_cols = False
177
178 for line in mlst_res_fh:
179 cols = line.strip().split("\t")
180 acc = acc_pat.findall(cols[mlst_acc_col])
181 if len(acc) > 1:
182 logging.error(f"Found more than 1 accession in column:\ncols[mlst_acc_col]\n")
183 exit(1)
184 else:
185 acc = "".join(acc)
186 if len(cols) == acceptable_num_mlst_cols and re.match(r"\d+|\-", cols[mlst_st_col]):
187 mlst_res_has_10_cols = True
188 if re.match(r"\-", cols[mlst_st_col]):
189 mlst_sts[acc] = "NULL"
190 else:
191 mlst_sts[acc] = cols[mlst_st_col]
192
193 if not mlst_res_has_10_cols:
194 logging.error(
195 "Requested to incorporate MLST ST's but file"
196 + f"\n{os.path.basename(mlst_res)}"
197 + "\ndoes not have 10 columns in all rows."
198 )
199 exit(1)
200
201 mlst_res_fh.close()
202
203 with open(pdg_acc_all, "r") as pdg_acc_all_fh:
204 for a in pdg_acc_all_fh.readlines():
205 num_accs_check.append(a.strip())
206
207 if not mcols_pat.match(mcols):
208 logging.error(
209 f"Supplied columns' names should only be"
210 + "\nalphanumeric (including _) separated by a comma."
211 )
212 exit(1)
213 else:
214 mcols = re.sub("\n", "", mcols).split(",")
215
216 if (
217 pdg_snp_meta_file
218 and os.path.exists(pdg_snp_meta_file)
219 and os.path.getsize(pdg_snp_meta_file) > 0
220 ):
221 acc2snp = defaultdict()
222 acc2meta = defaultdict(defaultdict)
223 init_pickled_sero = os.path.join(os.getcwd(), out_prefix + ".pickle")
224
225 if (
226 os.path.exists(init_pickled_sero)
227 and os.path.getsize(init_pickled_sero)
228 and not f_write_pick
229 ):
230 logging.error(
231 f"File {os.path.basename(init_pickled_sero)} already exists in\n{os.getcwd()}\n"
232 + "Use -fs to force overwrite it."
233 )
234 exit(1)
235
236 with open(pdg_snp_meta_file, "r") as snp_meta:
237 header = snp_meta.readline()
238 skipped_acc2snp = set()
239 for line in snp_meta:
240 cols = line.strip().split(pdg_meta_fs)
241 if not 4 <= len(cols) < 5:
242 logging.error(
243 f"The metadata file {pdg_snp_meta_file} is malformed.\n"
244 + f"Expected 4 columns. Got {len(cols)} columns.\n"
245 )
246 exit(1)
247
248 if re.match("NULL", cols[3]):
249 skipped_acc2snp.add(f"Isolate {cols[1]} has no genome accession: {cols[3]}")
250 elif not acc_pat.match(cols[3]):
251 logging.error(
252 f"Did not find accession in either field number 4\n"
253 + "or field number 10 of column 4."
254 + f"\nLine: {line}"
255 )
256 exit(1)
257 elif not re.match("NULL", cols[3]):
258 acc2snp[cols[3]] = cols[0]
259
260 if len(skipped_acc2snp) > 0:
261 logging.info(
262 f"While indexing\n{os.path.basename(pdg_snp_meta_file)},"
263 + "\nthese isolates were skipped:\n\n"
264 + "\n".join(skipped_acc2snp)
265 )
266
267 with open(pdg_meta_file, "r") as pdg_meta:
268 header = pdg_meta.readline().strip().split(pdg_meta_fs)
269 user_req_cols = [mcol_i for mcol_i, mcol in enumerate(header) if mcol in mcols]
270 cols_not_found = [mcol for mcol in mcols if mcol not in header]
271 null_wgs_accs = set()
272 if len(cols_not_found) > 0:
273 logging.error(
274 f"The following columns do not exist in the"
275 + f"\nmetadata file [ {os.path.basename(pdg_meta_file)} ]:\n"
276 + "".join(cols_not_found)
277 )
278 exit(1)
279
280 for line in pdg_meta.readlines():
281 cols = line.strip().split(pdg_meta_fs)
282 pdg_assm_acc = cols[acc_col]
283 if not acc_pat.match(pdg_assm_acc):
284 null_wgs_accs.add(
285 f"Isolate {cols[target_acc_col]} has no genome accession: {pdg_assm_acc}"
286 )
287 continue
288
289 if pdg_assm_acc in mlst_sts.keys():
290 acc2meta[pdg_assm_acc].setdefault("mlst_sequence_type", []).append(
291 str(mlst_sts[pdg_assm_acc])
292 )
293
294 for col in user_req_cols:
295 acc2meta[pdg_assm_acc].setdefault(header[col], []).append(str(cols[col]))
296
297 if len(null_wgs_accs) > 0:
298 logging.info(
299 f"While indexing\n{os.path.basename(pdg_meta_file)},"
300 + "\nthese isolates were skipped:\n\n"
301 + "\n".join(null_wgs_accs)
302 )
303
304 with open(init_pickled_sero, "wb") as write_pickled_sero:
305 pickle.dump(file=write_pickled_sero, obj=acc2meta)
306
307 if len(num_accs_check) != len(acc2meta.keys()):
308 logging.error(
309 "Failed the accession count check."
310 + f"\nExpected {len(num_accs_check)} accessions but got {len(acc2meta.keys())}."
311 )
312 exit(1)
313 else:
314 logging.info(
315 f"Number of valid accessions: {len(num_accs_check)}"
316 + f"\nNumber of accessions indexed: {len(acc2meta.keys())}"
317 + f"\nNumber of accessions participating in any of the SNP Clusters: {len(acc2snp.keys())}"
318 + f"\n\nCreated the pickle file for\n{os.path.basename(pdg_meta_file)}."
319 + "\nThis was the only requested function."
320 )
321
322 snp_meta.close()
323 write_pickled_sero.close()
324 exit(0)
325 elif pdg_meta_file and not (
326 os.path.exists(pdg_meta_file) and os.path.getsize(pdg_meta_file) > 0
327 ):
328 logging.error(
329 "Requested to create pickle from metadata, but\n"
330 + f"the file, {os.path.basename(pdg_meta_file)} is empty or\ndoes not exist!"
331 )
332 exit(1)
333
334 pdg_acc_all_fh.close()
335 snp_meta.close()
336 pdg_meta.close()
337 write_pickled_sero.close()
338
339
340 if __name__ == "__main__":
341 main()