gene-database

name	gene-database
description	Query the NCBI Gene database via E-utilities and the NCBI Datasets API; use it when you need to search genes by symbol/ID and retrieve annotations (RefSeq, GO, location, phenotype) for single or batch gene lists.
license	MIT
author	AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

• You have a gene symbol (e.g., BRCA1) and need the correct NCBI Gene ID for a specific organism.
• You have an NCBI Gene ID and need consolidated metadata (aliases, RefSeq accessions, genomic location, GO, literature links).
• You need to annotate a gene panel (dozens to thousands of genes) with consistent identifiers and core annotations.
• You want to search genes by biological context (GO terms, phenotype/disease keywords, pathway terms) and then retrieve details for the hits.
• You are building a pipeline that must respect NCBI rate limits and handle retries for transient API failures.

Key Features

• Symbol/name search with organism scoping using E-utilities (ESearch).
• Gene record retrieval by ID using E-utilities (EFetch/ESummary) in JSON/XML/text-oriented outputs.
• Streamlined, gene-focused retrieval using the NCBI Datasets API (metadata + sequences/links in a single workflow).
• Batch lookup utilities with basic rate-limit awareness and output aggregation.
• Supports common annotation fields: nomenclature/aliases, RefSeq transcripts/proteins, genomic location, GO annotations, phenotype/disease keywords, and related literature references.

Dependencies

• Python 3.9+
• requests >= 2.28
• NCBI E-utilities (Entrez) HTTP API (public service)
• NCBI Datasets HTTP API (public service)
• Optional: NCBI API key (recommended for higher throughput)

Example Usage

The following examples assume the repository provides these scripts:

• scripts/query_gene.py
• scripts/fetch_gene_data.py
• scripts/batch_gene_lookup.py

1) Search by symbol/name (E-utilities / ESearch)

python scripts/query_gene.py --search "BRCA1" --organism "human"

Example advanced query strings:

python scripts/query_gene.py --search "insulin[gene name] AND human[organism]"
python scripts/query_gene.py --search "dystrophin[gene name] AND muscular dystrophy[disease]"
python scripts/query_gene.py --search "human[organism] AND 17q21[chromosome]"

2) Retrieve gene information by Gene ID

Using E-utilities (format-oriented retrieval):

python scripts/query_gene.py --id 672 --format json

Using NCBI Datasets API (consolidated gene payload):

python scripts/fetch_gene_data.py --gene-id 672

Or by symbol + taxon:

python scripts/fetch_gene_data.py --symbol BRCA1 --taxon human
python scripts/fetch_gene_data.py --symbol TP53 --taxon "Homo sapiens" --output json

3) Batch lookup for gene list annotation

From a file of symbols (organism required for symbol disambiguation):

python scripts/batch_gene_lookup.py --file gene_list.txt --organism human

From a comma-separated list of Gene IDs:

python scripts/batch_gene_lookup.py --ids 672,7157,5594 --output results.json

Implementation Details

API selection guidance

• Use E-utilities when you need:
  • complex Entrez query syntax (fielded queries, boolean logic),
  • cross-database patterns,
  • fine control over search and retrieval steps (ESearch → ESummary/EFetch).
• Use NCBI Datasets API when you need:
  • a streamlined gene-centric retrieval path,
  • consolidated metadata (and often sequence-related links) with fewer round trips.

Query patterns (E-utilities)

Typical fielded query components include:

• "<SYMBOL>" plus organism scoping: BRCA1[gene name] AND human[organism]
• GO term searches (example): GO:0006915[biological process]
• Phenotype/disease keywords (example): diabetes[phenotype] AND mouse[organism]
• Pathway keywords (example): insulin signaling pathway[pathway]

Rate limits and API keys

• Without an API key (typical defaults):
  • E-utilities: ~3 requests/sec
  • Datasets API: ~5 requests/sec
• With an NCBI API key:
  • both can be used up to ~10 requests/sec (service-dependent)

Obtain an API key from: https://www.ncbi.nlm.nih.gov/account/

Error handling recommendations

• Handle standard HTTP errors:
  • 400: invalid/malformed query or parameters
  • 404: Gene ID not found
  • 429: rate limit exceeded
• Use exponential backoff with jitter for retries on 429/5xx.
• Cache results for repeated lookups (especially in batch annotation workflows).

Output/data formats

Depending on endpoint/script options, gene data may be returned as:

• JSON (recommended for pipelines)
• XML (legacy/verbose metadata)
• Text summaries
• Sequence-oriented formats such as FASTA or GenBank (when supported by the chosen endpoint/workflow)

Additional references

If present in the repository, consult:

• references/api_reference.md for endpoint/parameter details and response structures
• references/common_workflows.md for additional query patterns and end-to-end examples