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ncbi_gene

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Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

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NCBI Gene Database

Overview

NCBI Gene is a comprehensive database integrating gene information from diverse species. It provides nomenclature, reference sequences (RefSeqs), chromosomal maps, biological pathways, genetic variations, phenotypes, and cross-references to global genomic resources. In this project the agent exposes 3 download tools: fetch gene data by ID or symbol (Datasets API), and batch lookup by symbols. For finer control, ncbi_operations.py also provides E-utilities download/query functions (esearch, esummary, efetch) and additional batch operations. All download/query functions return rich JSON {status, file_info/content, content_preview, biological_metadata, execution_context}.

When to Use This Skill

This skill should be used when working with gene data including searching by gene symbol or ID, retrieving gene sequences and metadata, analyzing gene functions and pathways, or performing batch gene lookups.

Quick Start

The skill provides:

  1. Project modules in src/tools/database/ncbi/: fetch_gene_data.py (Datasets API), query_gene.py (E-utilities), batch_gene_lookup.py (batch operations), ncbi_operations.py (query/download operations); gene download functions re-exported via package.
  2. References: references/api_reference.md, references/common_workflows.md

NCBI provides two main APIs:

  • Datasets API — Optimized for gene data retrieval; used by download_ncbi_gene_by_id and download_ncbi_gene_by_symbol tools
  • E-utilities — Full-featured API for complex queries; used by the esearch/esummary/efetch programmatic functions

Agent Tools (Download Only)

Tool nameArgumentsPurpose
download_ncbi_gene_by_idgene_id, out_pathDownload gene data by NCBI Gene ID (Datasets API) to JSON
download_ncbi_gene_by_symbolsymbol, taxon, out_pathDownload gene data by symbol and organism (Datasets API) to JSON
download_ncbi_batch_lookup_by_symbolsgene_symbols, organism, out_pathBatch lookup multiple genes by symbols to JSON

Also available as general NCBI tools (useful in gene workflows):

Tool nameArgumentsPurpose
download_ncbi_sequencencbi_id, out_path, db (optional)Download NCBI sequence by accession (FASTA)
download_ncbi_metadatancbi_id, out_path, db, rettype (optional)Download NCBI metadata (GenBank/XML)
download_ncbi_blastsequence, out_path, program, database, etc.Submit BLAST search and download XML

Project Modules (Programmatic Use)

CapabilityFunctionModulePurpose
Fetch by IDfetch_gene_by_id(gene_id, api_key)fetch_gene_data.pyDatasets API: gene data as dict
Fetch by symbolfetch_gene_by_symbol(symbol, taxon, api_key)fetch_gene_data.pyDatasets API: gene data as dict
Fetch multiplefetch_multiple_genes(gene_ids, api_key)fetch_gene_data.pyDatasets API: multiple genes at once
Taxon lookupget_taxon_id(taxon_name)fetch_gene_data.pyConvert name to NCBI taxon ID
E-util searchesearch(query, retmax, api_key)query_gene.pySearch Gene DB, returns Gene IDs
E-util summaryesummary(gene_ids, api_key)query_gene.pyGet document summaries by Gene IDs
E-util fetchefetch(gene_ids, retmode, api_key)query_gene.pyFetch full gene records (XML/text)
Search+summarizesearch_and_summarize(query, organism, max_results, api_key)query_gene.pyConvenience: search + display
Batch searchbatch_esearch(queries, organism, api_key)batch_gene_lookup.pySearch multiple symbols → ID map
Batch summarybatch_esummary(gene_ids, api_key, chunk_size)batch_gene_lookup.pySummaries in chunks
Batch by IDsbatch_lookup_by_ids(gene_ids, api_key)batch_gene_lookup.pyStructured gene data by IDs
Batch by symbolsbatch_lookup_by_symbols(gene_symbols, organism, api_key)batch_gene_lookup.pyStructured gene data by symbols
Query: by IDquery_ncbi_gene_by_id(gene_id)ncbi_operations.pyReturns rich JSON in memory
Query: by symbolquery_ncbi_gene_by_symbol(symbol, taxon)ncbi_operations.pyReturns rich JSON in memory
Query: esearchquery_ncbi_gene_esearch(query, retmax)ncbi_operations.pyReturns rich JSON in memory
Query: esummaryquery_ncbi_gene_esummary(gene_ids)ncbi_operations.pyReturns rich JSON in memory
Query: efetchquery_ncbi_gene_efetch(gene_ids, retmode)ncbi_operations.pyReturns rich JSON in memory
Query: batch searchquery_ncbi_batch_esearch(queries, organism)ncbi_operations.pyReturns rich JSON in memory
Query: batch by IDsquery_ncbi_batch_lookup_by_ids(gene_ids)ncbi_operations.pyReturns rich JSON in memory
Query: batch by symbolsquery_ncbi_batch_lookup_by_symbols(gene_symbols, organism)ncbi_operations.pyReturns rich JSON in memory
Download: by IDdownload_ncbi_gene_by_id(gene_id, out_path)ncbi_operations.pySave to file, return rich JSON
Download: by symboldownload_ncbi_gene_by_symbol(symbol, taxon, out_path)ncbi_operations.pySave to file, return rich JSON
Download: esearchdownload_ncbi_gene_esearch(query, out_path, retmax)ncbi_operations.pySave to file, return rich JSON
Download: esummarydownload_ncbi_gene_esummary(gene_ids, out_path)ncbi_operations.pySave to file, return rich JSON
Download: efetchdownload_ncbi_gene_efetch(gene_ids, out_path, retmode)ncbi_operations.pySave to file, return rich JSON
Download: batch searchdownload_ncbi_batch_esearch(queries, out_path, organism)ncbi_operations.pySave to file, return rich JSON
Download: batch by IDsdownload_ncbi_batch_lookup_by_ids(gene_ids, out_path)ncbi_operations.pySave to file, return rich JSON
Download: batch by symbolsdownload_ncbi_batch_lookup_by_symbols(gene_symbols, organism, out_path)ncbi_operations.pySave to file, return rich JSON

Core Capabilities

1. Download Gene by ID (Datasets API)

from src.tools.database.ncbi import download_ncbi_gene_by_id

result = download_ncbi_gene_by_id("672", "output/ncbi_gene_brca1.json")
# Returns rich JSON with gene metadata, RefSeqs, GO annotations, etc.

2. Download Gene by Symbol (Datasets API)

from src.tools.database.ncbi import download_ncbi_gene_by_symbol

result = download_ncbi_gene_by_symbol("BRCA1", "human", "output/ncbi_gene_brca1_by_symbol.json")
result = download_ncbi_gene_by_symbol("TP53", "Homo sapiens", "output/ncbi_gene_tp53.json")

3. Batch Lookup by Symbols

from src.tools.database.ncbi import download_ncbi_batch_lookup_by_symbols

result = download_ncbi_batch_lookup_by_symbols(
    ["BRCA1", "TP53", "EGFR"], "human", "output/ncbi_genes_batch.json"
)

4. E-utilities Workflow (programmatic)

from src.tools.database.ncbi.ncbi_operations import (
    query_ncbi_gene_esearch,
    download_ncbi_gene_esummary,
    download_ncbi_gene_efetch,
)

# Step 1: Search for gene IDs
esearch_result = query_ncbi_gene_esearch("BRCA1[gene] AND human[organism]", retmax=10)

# Step 2: Download summaries or full records
download_ncbi_gene_esummary(["672", "7157"], "output/gene_summaries.json")
download_ncbi_gene_efetch(["672"], "output/gene_full_record.xml")

5. Low-Level Direct Access (programmatic)

from src.tools.database.ncbi.fetch_gene_data import fetch_gene_by_id, fetch_gene_by_symbol
from src.tools.database.ncbi.query_gene import esearch, esummary, efetch
from src.tools.database.ncbi.batch_gene_lookup import batch_lookup_by_symbols

# Datasets API
gene_data = fetch_gene_by_id("672")
gene_data = fetch_gene_by_symbol("BRCA1", "human")

# E-utilities
gene_ids = esearch("insulin[gene] AND human[organism]")
summaries = esummary(gene_ids)
records = efetch(gene_ids, retmode="xml")

# Batch
results = batch_lookup_by_symbols(["BRCA1", "TP53"], "human")

Common Workflows

Workflow 1: Gene Annotation (download)

from src.tools.database.ncbi import (
    download_ncbi_gene_by_symbol,
    download_ncbi_batch_lookup_by_symbols,
)

# Single gene
download_ncbi_gene_by_symbol("BRCA1", "human", "output/brca1_annotation.json")

# Gene panel
download_ncbi_batch_lookup_by_symbols(
    ["BRCA1", "BRCA2", "TP53", "PTEN", "ATM"], "human", "output/cancer_panel.json"
)

Workflow 2: Gene Search and Retrieve (programmatic)

from src.tools.database.ncbi.ncbi_operations import (
    query_ncbi_gene_esearch,
    download_ncbi_gene_by_id,
)
import json

# Search by complex query
result = query_ncbi_gene_esearch("p53 AND human[organism]", retmax=5)
parsed = json.loads(result)

# Download details for each hit
if parsed.get("status") == "success":
    content = json.loads(parsed["content"])
    for gene_id in content.get("gene_ids", []):
        download_ncbi_gene_by_id(str(gene_id), f"output/gene_{gene_id}.json")

Workflow 3: Cross-Database Integration

from src.tools.database.ncbi import (
    download_ncbi_gene_by_id,
    download_ncbi_sequence,
    download_ncbi_metadata,
)

# Step 1: Get comprehensive gene info
download_ncbi_gene_by_id("672", "output/brca1_gene_info.json")

# Step 2: Download protein sequence
download_ncbi_sequence("NP_009225.1", "output/brca1_protein.fasta", db="protein")

# Step 3: Download GenBank metadata
download_ncbi_metadata("NP_009225.1", "output/brca1_metadata.gb", db="protein")

Search Query Patterns

Example E-utilities query patterns for NCBI Gene:

  • Gene symbol: insulin[gene name] AND human[organism]
  • Gene with disease: dystrophin[gene name] AND muscular dystrophy[disease]
  • Chromosome location: human[organism] AND 17q21[chromosome]
  • GO term: GO:0006915[biological process] (apoptosis)
  • Phenotype: diabetes[phenotype] AND mouse[organism]
  • Pathway: insulin signaling pathway[pathway]

API Access

Rate Limits:

  • Without API key: 3 requests/second for E-utilities, 5 requests/second for Datasets API
  • With API key: 10 requests/second for both APIs

Authentication: Register for a free NCBI API key at https://www.ncbi.nlm.nih.gov/account/ to increase rate limits.

Data Formats

NCBI Gene data can be retrieved in multiple formats:

FormatUse case
JSONModern applications, programmatic processing
XMLLegacy systems, detailed metadata
GenBankSequence data with annotations
FASTASequence analysis workflows

Best Practices

  1. Always specify organism when searching by gene symbol to avoid ambiguity
  2. Use Gene IDs for precise lookups when available
  3. Batch requests when working with multiple genes to minimize API calls
  4. Cache results locally to reduce redundant queries
  5. Include API key in environment for higher rate limits
  6. Handle errors gracefully with retry logic for transient failures

Resources

Helper Scripts

  • fetch_gene_data.py — NCBI Datasets API: fetch_gene_by_id(), fetch_gene_by_symbol(), fetch_multiple_genes()
  • query_gene.py — E-utilities: esearch(), esummary(), efetch(), search_and_summarize()
  • batch_gene_lookup.py — Batch: batch_esearch(), batch_esummary(), batch_lookup_by_ids(), batch_lookup_by_symbols()

Reference Documentation

  • references/api_reference.md — E-utilities and Datasets API documentation, endpoints, parameters, response formats
  • references/common_workflows.md — Additional examples and use case patterns