bio-geo-data

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

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Install skill "bio-geo-data" with this command: npx skills add gptomics/bioskills/gptomics-bioskills-bio-geo-data

GEO Data

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

Required Setup

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)

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)

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

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

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

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

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

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

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.

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

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:

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

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

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

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