Agent skill

bio-geo-data

View SKILL.md on GitHub Repository
Stars 2,009
Forks 275

Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-geo-data

SKILL.md

name: bio-geo-data description: Query NCBI Gene Expression Omnibus (GEO) for expression datasets using Biopython Bio.Entrez. Use when finding microarray/RNA-seq datasets, downloading expression data, or linking GEO series to SRA runs. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

GEO Data

Query and access Gene Expression Omnibus datasets using Biopython's Entrez module.

Required Setup

python
from Bio import Entrez

Entrez.email = 'your.email@example.com'  # Required by NCBI
Entrez.api_key = 'your_api_key'          # Optional

GEO Database Types

Database db value Description
GEO DataSets gds Curated datasets (GDS*)
GEO Profiles geoprofiles Individual gene profiles

GEO Record Types:

Prefix Type Description
GSE Series Complete study/experiment
GSM Sample Individual sample
GPL Platform Array/sequencing platform
GDS DataSet Curated, normalized dataset

Searching GEO

Search GEO DataSets (GDS)

python
from Bio import Entrez

Entrez.email = 'your.email@example.com'

# Search curated datasets
handle = Entrez.esearch(db='gds', term='breast cancer AND Homo sapiens[orgn]', retmax=10)
record = Entrez.read(handle)
handle.close()

print(f"Found {record['Count']} datasets")
print(f"IDs: {record['IdList']}")

Search GEO Series (GSE)

python
# Search GEO Series via gds database
# Use entry_type filter
handle = Entrez.esearch(db='gds', term='RNA-seq[title] AND human[orgn] AND gse[entry_type]', retmax=10)
record = Entrez.read(handle)
handle.close()

Common Search Fields

Field Description Example
[orgn] Organism human[orgn]
[title] Dataset title breast cancer[title]
[description] Description text stem cell[description]
[platform] Platform GPL GPL570[platform]
[entry_type] Record type gse[entry_type], gds[entry_type]
[gdstype] Study type expression profiling[gdstype]
[pubmed] PubMed ID 35412348[pubmed]
[pdat] Publication date 2024[pdat]

GDS Types

python
# Expression profiling by array
term = 'expression profiling by array[gdstype] AND cancer'

# RNA-seq expression
term = 'expression profiling by high throughput sequencing[gdstype]'

# ChIP-seq
term = 'genome binding/occupancy profiling[gdstype]'

Fetching GEO Information

Get GEO DataSet Summary

python
# Fetch summary for GDS records
handle = Entrez.esummary(db='gds', id='200024320')
record = Entrez.read(handle)
handle.close()

summary = record[0]
print(f"Accession: {summary['Accession']}")
print(f"Title: {summary['title']}")
print(f"Summary: {summary['summary'][:200]}...")
print(f"Organism: {summary['taxon']}")
print(f"Platform: {summary['GPL']}")
print(f"Samples: {summary['n_samples']}")

Summary Fields

python
summary['Accession']     # GSE/GDS accession
summary['title']         # Dataset title
summary['summary']       # Description
summary['taxon']         # Organism
summary['GPL']           # Platform ID
summary['n_samples']     # Number of samples
summary['FTPLink']       # FTP download link
summary['PubMedIds']     # Associated publications
summary['gdsType']       # Dataset type
summary['ptechType']     # Platform technology

Code Patterns

Search and List GEO Series

python
from Bio import Entrez

Entrez.email = 'your.email@example.com'

def search_geo(term, entry_type='gse', max_results=20):
    full_term = f'{term} AND {entry_type}[entry_type]'
    handle = Entrez.esearch(db='gds', term=full_term, retmax=max_results)
    search = Entrez.read(handle)
    handle.close()

    if not search['IdList']:
        return []

    handle = Entrez.esummary(db='gds', id=','.join(search['IdList']))
    summaries = Entrez.read(handle)
    handle.close()

    results = []
    for s in summaries:
        results.append({
            'accession': s['Accession'],
            'title': s['title'],
            'organism': s['taxon'],
            'samples': s['n_samples'],
            'platform': s['GPL']
        })
    return results

datasets = search_geo('breast cancer RNA-seq AND human[orgn]')
for ds in datasets:
    print(f"{ds['accession']}: {ds['title'][:60]}... ({ds['samples']} samples)")

Find RNA-Seq Datasets

python
def find_rnaseq_datasets(organism, keywords, max_results=20):
    term = f'{keywords} AND {organism}[orgn] AND expression profiling by high throughput sequencing[gdstype] AND gse[entry_type]'

    handle = Entrez.esearch(db='gds', term=term, retmax=max_results)
    search = Entrez.read(handle)
    handle.close()

    if not search['IdList']:
        return []

    handle = Entrez.esummary(db='gds', id=','.join(search['IdList']))
    summaries = Entrez.read(handle)
    handle.close()

    return summaries

datasets = find_rnaseq_datasets('Homo sapiens', 'COVID-19')
for ds in datasets:
    print(f"{ds['Accession']}: {ds['n_samples']} samples - {ds['title'][:50]}...")

Get GSE Download Link

python
def get_geo_ftp(gse_accession):
    '''Get FTP download link for a GSE'''
    handle = Entrez.esearch(db='gds', term=f'{gse_accession}[accn]')
    search = Entrez.read(handle)
    handle.close()

    if not search['IdList']:
        return None

    handle = Entrez.esummary(db='gds', id=search['IdList'][0])
    summary = Entrez.read(handle)[0]
    handle.close()

    return summary.get('FTPLink')

ftp_link = get_geo_ftp('GSE123456')
print(f"Download from: {ftp_link}")

Link GEO to SRA

Many GEO RNA-seq datasets have associated SRA data.

python
def geo_to_sra(gse_accession):
    '''Find SRA runs associated with a GEO series'''
    # Search GEO
    handle = Entrez.esearch(db='gds', term=f'{gse_accession}[accn]')
    search = Entrez.read(handle)
    handle.close()

    if not search['IdList']:
        return []

    # Link to SRA
    handle = Entrez.elink(dbfrom='gds', db='sra', id=search['IdList'][0])
    links = Entrez.read(handle)
    handle.close()

    if not links[0]['LinkSetDb']:
        return []

    sra_ids = [link['Id'] for link in links[0]['LinkSetDb'][0]['Link']]

    # Get SRA accessions
    handle = Entrez.esummary(db='sra', id=','.join(sra_ids[:50]))
    summaries = Entrez.read(handle)
    handle.close()

    runs = []
    for s in summaries:
        expxml = s.get('ExpXml', '')
        if 'SRR' in str(expxml) or 'SRX' in str(expxml):
            runs.append(s)
    return runs

sra_data = geo_to_sra('GSE123456')
print(f"Found {len(sra_data)} SRA records")

Search by PubMed ID

python
def geo_from_pubmed(pmid):
    '''Find GEO datasets associated with a publication'''
    handle = Entrez.elink(dbfrom='pubmed', db='gds', id=pmid)
    links = Entrez.read(handle)
    handle.close()

    if not links[0]['LinkSetDb']:
        return []

    gds_ids = [link['Id'] for link in links[0]['LinkSetDb'][0]['Link']]

    handle = Entrez.esummary(db='gds', id=','.join(gds_ids))
    summaries = Entrez.read(handle)
    handle.close()

    return summaries

datasets = geo_from_pubmed('35412348')
for ds in datasets:
    print(f"{ds['Accession']}: {ds['title']}")

Download GEO Data (GEOparse)

For full data parsing, use the GEOparse library:

python
# pip install GEOparse
import GEOparse

# Download and parse GSE
gse = GEOparse.get_GEO('GSE123456')

# Access metadata
print(f"Title: {gse.metadata['title'][0]}")
print(f"Samples: {len(gse.gsms)}")

# Get sample metadata
for gsm_name, gsm in gse.gsms.items():
    print(f"{gsm_name}: {gsm.metadata['title'][0]}")

# Get expression table
if gse.gpls:
    gpl_name = list(gse.gpls.keys())[0]
    expression_table = gse.pivot_samples('VALUE')

Download Options

Direct FTP Download

bash
# Download entire GSE
wget -r -np -nd ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/

# Download specific file types
wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/suppl/*counts*.txt.gz

Series Matrix Files

python
import gzip
import urllib.request

def download_series_matrix(gse):
    '''Download series matrix file'''
    gse_prefix = gse[:len(gse)-3] + 'nnn'
    url = f'https://ftp.ncbi.nlm.nih.gov/geo/series/{gse_prefix}/{gse}/matrix/{gse}_series_matrix.txt.gz'

    filename = f'{gse}_series_matrix.txt.gz'
    urllib.request.urlretrieve(url, filename)
    return filename

Common Errors

Error Cause Solution
Empty results Wrong entry_type Add gse[entry_type] or gds[entry_type]
No FTPLink Superseries or no data Check if series has supplementary files
No SRA link Microarray data SRA only for sequencing data

Decision Tree

Need GEO expression data?
├── Looking for curated datasets?
│   └── Search gds with [entry_type]=gds
├── Looking for any experiment?
│   └── Search gds with [entry_type]=gse
├── Want RNA-seq specifically?
│   └── Add 'expression profiling by high throughput sequencing[gdstype]'
├── Have a publication?
│   └── Link pubmed -> gds
├── Need raw sequencing data?
│   └── Link gds -> sra, then use sra-data skill
├── Need processed expression matrix?
│   └── Download series matrix or use GEOparse
└── Need full metadata?
    └── Use GEOparse library

Related Skills

  • entrez-search - General database searching
  • entrez-link - Link GEO to SRA and other databases
  • sra-data - Download raw sequencing data from linked SRA
  • batch-downloads - Download multiple GEO records

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

FreedomIntelligence/OpenClaw-Medical-Skills

vcf-annotator

Annotate VCF variants with VEP, ClinVar, gnomAD frequencies, and ancestry-aware context. Generates prioritised variant reports.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

chemist-analyst

Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties, reaction pathways, synthesis, and analytical methods. Use when: Chemical reactions, material analysis, synthesis planning, process optimization, environmental chemistry. Evaluates: Molecular structure, reaction mechanisms, yield, selectivity, safety, environmental impact.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-alignment-io

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

sleep-analyzer

分析睡眠数据、识别睡眠模式、评估睡眠质量，并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-hi-c-analysis-matrix-operations

Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected matrices. Use when normalizing or transforming Hi-C matrices.

2,009 275
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results