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SKILL verified MIT Self-run

Query Geo

skill-cheatthegod-biohermes-query-geo · by cheatthegod

Query NCBI GEO for gene expression datasets. Use when user asks about RNA-seq datasets, microarray data, expression data, GEO accessions, or finding public datasets. Triggers on "geo", "gene expression omnibus", "expression dataset", "RNA-seq dataset", "microarray dataset", "GSE", "GDS".

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Install

$ agentstack add skill-cheatthegod-biohermes-query-geo

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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5mo ago

Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

NCBI GEO Database Query

Query Gene Expression Omnibus for public expression datasets.

When to Use

  • User wants to find RNA-seq or microarray datasets
  • User asks about gene expression studies for a disease/tissue
  • User provides a GEO accession (GSE/GDS) to look up
  • User wants to download expression data

How to Execute

from Bio import Entrez
import json

Entrez.email = "bioclaw@example.com"

# 1. Search GEO datasets
def search_geo(query, max_results=10, db="gds"):
    handle = Entrez.esearch(db=db, term=query, retmax=max_results, sort="relevance")
    record = Entrez.read(handle)
    handle.close()
    return record

# 2. Get dataset summaries
def geo_summary(id_list, db="gds"):
    ids = ",".join(str(i) for i in id_list)
    handle = Entrez.esummary(db=db, id=ids, retmode="json")
    result = json.loads(handle.read())
    handle.close()
    return result

# 3. Search for Series (GSE)
def search_gse(keyword, organism="Homo sapiens", max_results=10):
    query = f'"{keyword}" AND "{organism}"[Organism] AND gse[ETYP]'
    return search_geo(query, max_results)

# Example: Find breast cancer RNA-seq datasets
search = search_gse("breast cancer RNA-seq", max_results=5)
print(f"Found {search['Count']} datasets")

if search['IdList']:
    summaries = geo_summary(search['IdList'])
    for uid in search['IdList']:
        info = summaries['result'].get(str(uid), {})
        title = info.get('title', 'N/A')
        gse = info.get('accession', 'N/A')
        gpl = info.get('gpl', 'N/A')
        n_samples = info.get('n_samples', 'N/A')
        summary = info.get('summary', 'N/A')[:200]
        print(f"\n{gse}: {title}")
        print(f"  Platform: {gpl}, Samples: {n_samples}")
        print(f"  Summary: {summary}...")
        print(f"  URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc={gse}")

Search Syntax

  • By keyword: "CRISPR" AND gse[ETYP]
  • By organism: "Homo sapiens"[Organism]
  • By platform: "Illumina"[Platform]
  • By date: "2024/01:2026/12"[PDAT]
  • Combine: "breast cancer" AND "RNA-seq" AND "Homo sapiens"[Organism] AND gse[ETYP]

Follow-up Suggestions

  • "Want me to download the expression matrix for this dataset?"
  • "Should I do differential expression analysis?"
  • "Want me to check what genes are differentially expressed?"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.