#!/usr/bin/env python3
"""
Batch Identifier Converter
This script converts multiple identifiers between biological databases
using UniProt's mapping service. Supports batch processing with
automatic chunking and error handling.
Usage:
python batch_id_converter.py INPUT_FILE --from DB1 --to DB2 [options]
Examples:
python batch_id_converter.py uniprot_ids.txt --from UniProtKB_AC-ID --to KEGG
python batch_id_converter.py gene_ids.txt --from GeneID --to UniProtKB --output mapping.csv
python batch_id_converter.py ids.txt --from UniProtKB_AC-ID --to Ensembl --chunk-size 50
Input file format:
One identifier per line (plain text)
Common database codes:
UniProtKB_AC-ID - UniProt accession/ID
KEGG - KEGG gene IDs
GeneID - NCBI Gene (Entrez) IDs
Ensembl - Ensembl gene IDs
Ensembl_Protein - Ensembl protein IDs
RefSeq_Protein - RefSeq protein IDs
PDB - Protein Data Bank IDs
HGNC - Human gene symbols
GO - Gene Ontology IDs
"""
import sys
import argparse
import csv
import time
from bioservices import UniProt
# Common database code mappings
DATABASE_CODES = {
'uniprot': 'UniProtKB_AC-ID',
'uniprotkb': 'UniProtKB_AC-ID',
'kegg': 'KEGG',
'geneid': 'GeneID',
'entrez': 'GeneID',
'ensembl': 'Ensembl',
'ensembl_protein': 'Ensembl_Protein',
'ensembl_transcript': 'Ensembl_Transcript',
'refseq': 'RefSeq_Protein',
'refseq_protein': 'RefSeq_Protein',
'pdb': 'PDB',
'hgnc': 'HGNC',
'mgi': 'MGI',
'go': 'GO',
'pfam': 'Pfam',
'interpro': 'InterPro',
'reactome': 'Reactome',
'string': 'STRING',
'biogrid': 'BioGRID'
}
def normalize_database_code(code):
"""Normalize database code to official format."""
# Try exact match first
if code in DATABASE_CODES.values():
return code
# Try lowercase lookup
lowercase = code.lower()
if lowercase in DATABASE_CODES:
return DATABASE_CODES[lowercase]
# Return as-is if not found (may still be valid)
return code
def read_ids_from_file(filename):
"""Read identifiers from file (one per line)."""
print(f"Reading identifiers from {filename}...")
ids = []
with open(filename, 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('#'):
ids.append(line)
print(f"✓ Read {len(ids)} identifier(s)")
return ids
def batch_convert(ids, from_db, to_db, chunk_size=100, delay=0.5):
"""Convert IDs with automatic chunking and error handling."""
print(f"\nConverting {len(ids)} IDs:")
print(f" From: {from_db}")
print(f" To: {to_db}")
print(f" Chunk size: {chunk_size}")
print()
u = UniProt(verbose=False)
all_results = {}
failed_ids = []
total_chunks = (len(ids) + chunk_size - 1) // chunk_size
for i in range(0, len(ids), chunk_size):
chunk = ids[i:i+chunk_size]
chunk_num = (i // chunk_size) + 1
query = ",".join(chunk)
try:
print(f" [{chunk_num}/{total_chunks}] Processing {len(chunk)} IDs...", end=" ")
results = u.mapping(fr=from_db, to=to_db, query=query)
if results:
all_results.update(results)
mapped_count = len([v for v in results.values() if v])
print(f"✓ Mapped: {mapped_count}/{len(chunk)}")
else:
print(f"✗ No mappings returned")
failed_ids.extend(chunk)
# Rate limiting
if delay > 0 and i + chunk_size < len(ids):
time.sleep(delay)
except Exception as e:
print(f"✗ Error: {e}")
# Try individual IDs in failed chunk
print(f" Retrying individual IDs...")
for single_id in chunk:
try:
result = u.mapping(fr=from_db, to=to_db, query=single_id)
if result:
all_results.update(result)
print(f" ✓ {single_id}")
else:
failed_ids.append(single_id)
print(f" ✗ {single_id} - no mapping")
except Exception as e2:
failed_ids.append(single_id)
print(f" ✗ {single_id} - {e2}")
time.sleep(0.2)
# Add missing IDs to results (mark as failed)
for id_ in ids:
if id_ not in all_results:
all_results[id_] = None
print(f"\n✓ Conversion complete:")
print(f" Total: {len(ids)}")
print(f" Mapped: {len([v for v in all_results.values() if v])}")
print(f" Failed: {len(failed_ids)}")
return all_results, failed_ids
def save_mapping_csv(mapping, output_file, from_db, to_db):
"""Save mapping results to CSV."""
print(f"\nSaving results to {output_file}...")
with open(output_file, 'w', newline='') as f:
writer = csv.writer(f)
# Header
writer.writerow(['Source_ID', 'Source_DB', 'Target_IDs', 'Target_DB', 'Mapping_Status'])
# Data
for source_id, target_ids in sorted(mapping.items()):
if target_ids:
target_str = ";".join(target_ids)
status = "Success"
else:
target_str = ""
status = "Failed"
writer.writerow([source_id, from_db, target_str, to_db, status])
print(f"✓ Results saved")
def save_failed_ids(failed_ids, output_file):
"""Save failed IDs to file."""
if not failed_ids:
return
print(f"\nSaving failed IDs to {output_file}...")
with open(output_file, 'w') as f:
for id_ in failed_ids:
f.write(f"{id_}\n")
print(f"✓ Saved {len(failed_ids)} failed ID(s)")
def print_mapping_summary(mapping, from_db, to_db):
"""Print summary of mapping results."""
print(f"\n{'='*70}")
print("MAPPING SUMMARY")
print(f"{'='*70}")
total = len(mapping)
mapped = len([v for v in mapping.values() if v])
failed = total - mapped
print(f"\nSource database: {from_db}")
print(f"Target database: {to_db}")
print(f"\nTotal identifiers: {total}")
print(f"Successfully mapped: {mapped} ({mapped/total*100:.1f}%)")
print(f"Failed to map: {failed} ({failed/total*100:.1f}%)")
# Show some examples
if mapped > 0:
print(f"\nExample mappings (first 5):")
count = 0
for source_id, target_ids in mapping.items():
if target_ids:
target_str = ", ".join(target_ids[:3])
if len(target_ids) > 3:
target_str += f" ... +{len(target_ids)-3} more"
print(f" {source_id} → {target_str}")
count += 1
if count >= 5:
break
# Show multiple mapping statistics
multiple_mappings = [v for v in mapping.values() if v and len(v) > 1]
if multiple_mappings:
print(f"\nMultiple target mappings: {len(multiple_mappings)} ID(s)")
print(f" (These source IDs map to multiple target IDs)")
print(f"{'='*70}")
def list_common_databases():
"""Print list of common database codes."""
print("\nCommon Database Codes:")
print("-" * 70)
print(f"{'Alias':<20} {'Official Code':<30}")
print("-" * 70)
for alias, code in sorted(DATABASE_CODES.items()):
if alias != code.lower():
print(f"{alias:<20} {code:<30}")
print("-" * 70)
print("\nNote: Many other database codes are supported.")
print("See UniProt documentation for complete list.")
def main():
"""Main conversion workflow."""
parser = argparse.ArgumentParser(
description="Batch convert biological identifiers between databases",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
python batch_id_converter.py uniprot_ids.txt --from UniProtKB_AC-ID --to KEGG
python batch_id_converter.py ids.txt --from GeneID --to UniProtKB -o mapping.csv
python batch_id_converter.py ids.txt --from uniprot --to ensembl --chunk-size 50
Common database codes:
UniProtKB_AC-ID, KEGG, GeneID, Ensembl, Ensembl_Protein,
RefSeq_Protein, PDB, HGNC, GO, Pfam, InterPro, Reactome
Use --list-databases to see all supported aliases.
"""
)
parser.add_argument("input_file", help="Input file with IDs (one per line)")
parser.add_argument("--from", dest="from_db", required=True,
help="Source database code")
parser.add_argument("--to", dest="to_db", required=True,
help="Target database code")
parser.add_argument("-o", "--output", default=None,
help="Output CSV file (default: mapping_results.csv)")
parser.add_argument("--chunk-size", type=int, default=100,
help="Number of IDs per batch (default: 100)")
parser.add_argument("--delay", type=float, default=0.5,
help="Delay between batches in seconds (default: 0.5)")
parser.add_argument("--save-failed", action="store_true",
help="Save failed IDs to separate file")
parser.add_argument("--list-databases", action="store_true",
help="List common database codes and exit")
args = parser.parse_args()
# List databases and exit
if args.list_databases:
list_common_databases()
sys.exit(0)
print("=" * 70)
print("BIOSERVICES: Batch Identifier Converter")
print("=" * 70)
# Normalize database codes
from_db = normalize_database_code(args.from_db)
to_db = normalize_database_code(args.to_db)
if from_db != args.from_db:
print(f"\nNote: Normalized '{args.from_db}' → '{from_db}'")
if to_db != args.to_db:
print(f"Note: Normalized '{args.to_db}' → '{to_db}'")
# Read input IDs
try:
ids = read_ids_from_file(args.input_file)
except Exception as e:
print(f"\n✗ Error reading input file: {e}")
sys.exit(1)
if not ids:
print("\n✗ No IDs found in input file")
sys.exit(1)
# Perform conversion
mapping, failed_ids = batch_convert(
ids,
from_db,
to_db,
chunk_size=args.chunk_size,
delay=args.delay
)
# Print summary
print_mapping_summary(mapping, from_db, to_db)
# Save results
output_file = args.output or "mapping_results.csv"
save_mapping_csv(mapping, output_file, from_db, to_db)
# Save failed IDs if requested
if args.save_failed and failed_ids:
failed_file = output_file.replace(".csv", "_failed.txt")
save_failed_ids(failed_ids, failed_file)
print(f"\n✓ Done!")
if __name__ == "__main__":
main()