Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
npxskills add davila7/claude-code-templates--skill kegg-databaseLoading…
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive bioinformatics resource for biological pathway analysis and molecular interaction networks.
Important: KEGG API is made available only for academic use by academic users.
This skill should be used when querying pathways, genes, compounds, enzymes, diseases, and drugs across multiple organisms using KEGG's REST API.
The skill provides:
scripts/kegg_api.py) for all KEGG REST API operationsreferences/kegg_reference.md) with detailed API specificationsWhen users request KEGG data, determine which operation is needed and use the appropriate function from scripts/kegg_api.py.
kegg_info)Retrieve metadata and statistics about KEGG databases.
When to use: Understanding database structure, checking available data, getting release information.
Usage:
from scripts.kegg_api import kegg_info
# Get pathway database info
info = kegg_info('pathway')
# Get organism-specific info
hsa_info = kegg_info('hsa') # Human genome
Common databases: kegg, pathway, module, brite, genes, genome, compound, glycan, reaction, enzyme, disease, drug
kegg_list)List entry identifiers and names from KEGG databases.
When to use: Getting all pathways for an organism, listing genes, retrieving compound catalogs.
Usage:
from scripts.kegg_api import kegg_list
# List all reference pathways
pathways = kegg_list('pathway')
# List human-specific pathways
hsa_pathways = kegg_list('pathway', 'hsa')
# List specific genes (max 10)
genes = kegg_list('hsa:10458+hsa:10459')
Common organism codes: hsa (human), mmu (mouse), dme (fruit fly), sce (yeast), eco (E. coli)
kegg_find)Search KEGG databases by keywords or molecular properties.
When to use: Finding genes by name/description, searching compounds by formula or mass, discovering entries by keywords.
Usage:
from scripts.kegg_api import kegg_find
# Keyword search
results = kegg_find('genes', 'p53')
shiga_toxin = kegg_find('genes', 'shiga toxin')
# Chemical formula search (exact match)
compounds = kegg_find('compound', 'C7H10N4O2', 'formula')
# Molecular weight range search
drugs = kegg_find('drug', '300-310', 'exact_mass')
Search options: formula (exact match), exact_mass (range), mol_weight (range)
kegg_get)Get complete database entries or specific data formats.
When to use: Retrieving pathway details, getting gene/protein sequences, downloading pathway maps, accessing compound structures.
Usage:
from scripts.kegg_api import kegg_get
# Get pathway entry
pathway = kegg_get('hsa00010') # Glycolysis pathway
# Get multiple entries (max 10)
genes = kegg_get(['hsa:10458', 'hsa:10459'])
# Get protein sequence (FASTA)
sequence = kegg_get('hsa:10458', 'aaseq')
# Get nucleotide sequence
nt_seq = kegg_get('hsa:10458', 'ntseq')
# Get compound structure
mol_file = kegg_get('cpd:C00002', 'mol') # ATP in MOL format
# Get pathway as JSON (single entry only)
pathway_json = kegg_get('hsa05130', 'json')
# Get pathway image (single entry only)
pathway_img = kegg_get('hsa05130', 'image')
Output formats: aaseq (protein FASTA), ntseq (nucleotide FASTA), mol (MOL format), kcf (KCF format), image (PNG), kgml (XML), json (pathway JSON)
Important: Image, KGML, and JSON formats allow only one entry at a time.
kegg_conv)Convert identifiers between KEGG and external databases.
When to use: Integrating KEGG data with other databases, mapping gene IDs, converting compound identifiers.
Usage:
from scripts.kegg_api import kegg_conv
# Convert all human genes to NCBI Gene IDs
conversions = kegg_conv('ncbi-geneid', 'hsa')
# Convert specific gene
gene_id = kegg_conv('ncbi-geneid', 'hsa:10458')
# Convert to UniProt
uniprot_id = kegg_conv('uniprot', 'hsa:10458')
# Convert compounds to PubChem
pubchem_ids = kegg_conv('pubchem', 'compound')
# Reverse conversion (NCBI Gene ID to KEGG)
kegg_id = kegg_conv('hsa', 'ncbi-geneid')
Supported conversions: ncbi-geneid, ncbi-proteinid, uniprot, pubchem, chebi
kegg_link)Find related entries within and between KEGG databases.
When to use: Finding pathways containing genes, getting genes in a pathway, mapping genes to KO groups, finding compounds in pathways.
Usage:
from scripts.kegg_api import kegg_link
# Find pathways linked to human genes
pathways = kegg_link('pathway', 'hsa')
# Get genes in a specific pathway
genes = kegg_link('genes', 'hsa00010') # Glycolysis genes
# Find pathways containing a specific gene
gene_pathways = kegg_link('pathway', 'hsa:10458')
# Find compounds in a pathway
compounds = kegg_link('compound', 'hsa00010')
# Map genes to KO (orthology) groups
ko_groups = kegg_link('ko', 'hsa:10458')
Common links: genes ↔ pathway, pathway ↔ compound, pathway ↔ enzyme, genes ↔ ko (orthology)
kegg_ddi)Check for drug-drug interactions.
When to use: Analyzing drug combinations, checking for contraindications, pharmacological research.
Usage:
from scripts.kegg_api import kegg_ddi
# Check single drug
interactions = kegg_ddi('D00001')
# Check multiple drugs (max 10)
interactions = kegg_ddi(['D00001', 'D00002', 'D00003'])
Use case: Finding pathways associated with genes of interest (e.g., for pathway enrichment analysis).
from scripts.kegg_api import kegg_find, kegg_link, kegg_get
# Step 1: Find gene ID by name
gene_results = kegg_find('genes', 'p53')
# Step 2: Link gene to pathways
pathways = kegg_link('pathway', 'hsa:7157') # TP53 gene
# Step 3: Get detailed pathway information
for pathway_line in pathways.split('\n'):
if pathway_line:
pathway_id = pathway_line.split('\t')[1].replace('path:', '')
pathway_info = kegg_get(pathway_id)
# Process pathway information
Use case: Getting all genes in organism pathways for enrichment analysis.
from scripts.kegg_api import kegg_list, kegg_link
# Step 1: List all human pathways
pathways = kegg_list('pathway', 'hsa')
# Step 2: For each pathway, get associated genes
for pathway_line in pathways.split('\n'):
if pathway_line:
pathway_id = pathway_line.split('\t')[0]
genes = kegg_link('genes', pathway_id)
# Process genes for enrichment analysis
Use case: Finding metabolic pathways containing compounds of interest.
from scripts.kegg_api import kegg_find, kegg_link, kegg_get
# Step 1: Search for compound
compound_results = kegg_find('compound', 'glucose')
# Step 2: Link compound to reactions
reactions = kegg_link('reaction', 'cpd:C00031') # Glucose
# Step 3: Link reactions to pathways
pathways = kegg_link('pathway', 'rn:R00299') # Specific reaction
# Step 4: Get pathway details
pathway_info = kegg_get('map00010') # Glycolysis
Use case: Integrating KEGG data with UniProt, NCBI, or PubChem databases.
from scripts.kegg_api import kegg_conv, kegg_get
# Step 1: Convert KEGG gene IDs to external database IDs
uniprot_map = kegg_conv('uniprot', 'hsa')
ncbi_map = kegg_conv('ncbi-geneid', 'hsa')
# Step 2: Parse conversion results
for line in uniprot_map.split('\n'):
if line:
kegg_id, uniprot_id = line.split('\t')
# Use external IDs for integration
# Step 3: Get sequences using KEGG
sequence = kegg_get('hsa:10458', 'aaseq')
Use case: Comparing pathways across different organisms.
from scripts.kegg_api import kegg_list, kegg_get
# Step 1: List pathways for multiple organisms
human_pathways = kegg_list('pathway', 'hsa')
mouse_pathways = kegg_list('pathway', 'mmu')
yeast_pathways = kegg_list('pathway', 'sce')
# Step 2: Get reference pathway for comparison
ref_pathway = kegg_get('map00010') # Reference glycolysis
# Step 3: Get organism-specific versions
hsa_glycolysis = kegg_get('hsa00010')
mmu_glycolysis = kegg_get('mmu00010')
KEGG organizes pathways into seven major categories. When interpreting pathway IDs or recommending pathways to users:
map00010 - Glycolysis, map00190 - Oxidative phosphorylation)map03010 - Ribosome, map03040 - Spliceosome)map04010 - MAPK signaling, map02010 - ABC transporters)map04140 - Autophagy, map04210 - Apoptosis)map04610 - Complement cascade, map04910 - Insulin signaling)Reference references/kegg_reference.md for detailed pathway lists and classifications.
map##### - Reference pathway (generic, not organism-specific)hsa##### - Human pathwaymmu##### - Mouse pathwayorganism:gene_number (e.g., hsa:10458)cpd:C##### (e.g., cpd:C00002 for ATP)dr:D##### (e.g., dr:D00001)ec:EC_number (e.g., ec:1.1.1.1)ko:K##### (e.g., ko:K00001)Respect these constraints when using the KEGG API:
For comprehensive API documentation, database specifications, organism codes, and advanced usage, refer to references/kegg_reference.md. This includes:
404 Not Found: Entry or database doesn't exist; verify IDs and organism codes 400 Bad Request: Syntax error in API call; check parameter formatting Empty results: Search term may not match entries; try broader keywords Image/KGML errors: These formats only work with single entries; remove batch processing
For interactive pathway visualization and annotation:
map05200 - Pathways in cancer, map05010 - Alzheimer disease)
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