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author | zsloan | 2023-10-24 17:41:16 +0000 |
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committer | zsloan | 2023-10-24 17:41:16 +0000 |
commit | 79ce392c5a482a0460e8a91344a0e63c9e9a8085 (patch) | |
tree | 36299a0b54123e150783d86c5316d5f654c616a1 /scripts | |
parent | a9dcc1091a3b02c79e9e6625f22dced79ee0a1a5 (diff) | |
download | genenetwork2-79ce392c5a482a0460e8a91344a0e63c9e9a8085.tar.gz |
Add script for creating list of ProbeSet datasets with NAs for Max QTL
Diffstat (limited to 'scripts')
-rw-r--r-- | scripts/find_dbs_with_NAs.py | 54 |
1 files changed, 54 insertions, 0 deletions
diff --git a/scripts/find_dbs_with_NAs.py b/scripts/find_dbs_with_NAs.py new file mode 100644 index 00000000..a4ff3ee5 --- /dev/null +++ b/scripts/find_dbs_with_NAs.py @@ -0,0 +1,54 @@ +import os +from typing import Tuple +from urllib.parse import urlparse +import MySQLdb as mdb +from MySQLdb.cursors import DictCursor + +def parse_db_url(sql_uri: str) -> Tuple: + """function to parse SQL_URI""" + parsed_db = urlparse(sql_uri) + return ( + parsed_db.hostname, parsed_db.username, parsed_db.password, + parsed_db.path[1:], parsed_db.port) + +sql_uri = os.environ.get("SQL_URI") +host, user, passwd, db_name, port = parse_db_url(sql_uri) +conn = mdb.connect(db=db_name, + user=user, + passwd=passwd, + host=host, + port=port) + +query = ( + "SELECT psf.Id, psf.FullName " + "FROM ProbeSetXRef AS psx " + "INNER JOIN ProbeSetFreeze AS psf ON psx.ProbeSetFreezeId = psf.Id " + "INNER JOIN ProbeFreeze AS pf ON psf.ProbeFreezeId = pf.Id " + "INNER JOIN InbredSet AS ibs ON pf.InbredSetId = ibs.Id " + "WHERE psx.Locus IS NULL AND " + "ibs.MappingMethodId = 1" +) + +dataset_NAs_counts = {} +dataset_name_dict = {} # Mapping of IDs to names +with conn.cursor(cursorclass=DictCursor) as cursor: + cursor.execute(query) + for row in cursor.fetchall(): + dset_id = str(row['Id']) + if dset_id in dataset_NAs_counts: + dataset_NAs_counts[dset_id] += 1 + else: + dataset_NAs_counts[dset_id] = 1 + if dset_id not in dataset_name_dict: + dataset_name_dict[dset_id] = str(row['FullName']) + +sorted_NAs_counts = {k: v for k, v in sorted(dataset_NAs_counts.items(), key=lambda item: item[1], reverse=True)} + +output_path = os.path.join(os.environ.get("TMPDIR"), "filtered_NAs_list.csv") +with open(output_path, "w") as out_file: + out_file.write("ID\tFullName\tCount\n") + for dset_id in sorted_NAs_counts: + out_file.write("\t".join([str(dset_id), str(dataset_name_dict[dset_id]), str(sorted_NAs_counts[dset_id])]) + "\n") + + +
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