Datasets:
Formats:
parquet
Languages:
English
Size:
10M - 100M
Tags:
biology
chemistry
drug-discovery
clinical-trials
protein-protein-interaction
gene-essentiality
License:
File size: 1,214 Bytes
6d1bbc7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | #!/usr/bin/env python
"""Load STRING v12.0 zero-score negatives into PPI database (Bronze tier)."""
import argparse
from pathlib import Path
_PROJECT_ROOT = Path(__file__).resolve().parent.parent
def main():
parser = argparse.ArgumentParser(
description="Load STRING zero-score negatives into PPI DB"
)
parser.add_argument(
"--db-path", type=str, default=None, help="PPI database path"
)
parser.add_argument(
"--data-dir", type=str, default=None, help="STRING data directory"
)
parser.add_argument(
"--min-degree", type=int, default=5,
help="Minimum STRING degree for well-studied proteins (default: 5)",
)
parser.add_argument(
"--max-pairs", type=int, default=500_000,
help="Maximum negative pairs (default: 500000)",
)
args = parser.parse_args()
from negbiodb_ppi.etl_string import run_string_etl
stats = run_string_etl(
db_path=args.db_path,
data_dir=args.data_dir,
min_degree=args.min_degree,
max_pairs=args.max_pairs,
)
print("\nSTRING ETL complete:")
for k, v in stats.items():
print(f" {k}: {v:,}")
if __name__ == "__main__":
main()
|