geo-database
Explore NCBI GEO Expression Data
Researchers often need reliable ways to find and reuse public gene expression datasets. This skill guides Claude, Codex, and Claude Code through NCBI GEO search, retrieval, parsing, and analysis workflows.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "geo-database" from https://skillstore.io/skills/k-dense-ai-geo-database.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-geo-database/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "geo-database". Find GEO studies for breast cancer RNA-seq in humans.
Expected outcome:
A concise shortlist of candidate GEO Series, with organism, technology, sample context, and next steps for metadata review.
Using "geo-database". Explain what files I should download for GSE123456.
Expected outcome:
A plain-language comparison of series matrix, SOFT, MINiML, and supplementary files, with guidance on when each format is useful.
Using "geo-database". Plan a differential expression workflow for one GEO Series.
Expected outcome:
A stepwise analysis plan covering download, metadata checks, group assignment, expression extraction, quality control, testing, and citation notes.
Security Audit
SafeThe skill is primarily documentation and examples for accessing public NCBI GEO data. I confirmed the plaintext FTP guidance as a medium concern because it can expose downloads to tampering. The remaining static findings are false positives involving public URLs, Markdown fences, placeholder keys, local data saves, and GEO identifiers.
Capability review items (7)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Risk Factors
๐ Network access (26)
โ๏ธ External commands (39)
๐ Filesystem access (2)
๐ Env variables (1)
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<a href="https://skillstore.io/skills/k-dense-ai-geo-database?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-geo-database/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
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APA citation
K-Dense-AI. (2026). geo-database security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-geo-database/audits/9BibTeX citation
@techreport{k-dense-ai-k-dense-ai-geo-database-2026,
author = {K-Dense-AI},
title = {geo-database security audit report (audit version 9)},
institution = {Skillstore},
year = {2026},
number = {9},
url = {https://skillstore.io/skills/k-dense-ai-geo-database/audits/9},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "geo-database security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/k-dense-ai-geo-database/audits/9"
identifiers:
- type: other
value: "skillstore:k-dense-ai-geo-database:audit:9"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-geo-database
2026-08-21
k-dense-ai-geo-database
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Find disease expression studies
Search GEO for human disease datasets and summarize candidate GSE records for review.
Prepare expression matrices
Download a GEO Series, inspect sample metadata, and extract a matrix for downstream analysis.
Compare studies for a gene
Locate platform probes for a gene and compare expression summaries across selected studies.
Try These Prompts
Find NCBI GEO datasets about [condition] in [organism]. Return likely GSE accessions, study types, sample counts, and why each result is relevant.
Use GEO guidance to review [GSE accession]. Summarize the title, organism, platform, samples, experimental design, and available file types.
Create a workflow for downloading [GSE accession], extracting the expression matrix, separating control and treatment samples, and checking data quality.
Plan a reproducible GEO meta-analysis for [gene or pathway] across [GSE accessions]. Include metadata harmonization, probe mapping, normalization checks, and statistical cautions.
Best Practices
- Set an Entrez email address and respect NCBI rate limits for every automated query.
- Check sample metadata, platform annotation, and processing methods before comparing expression values.
- Cache large downloads locally and record dataset accessions, versions, and citations.
Avoid
- Do not assume all GEO studies use comparable normalization or experimental design.
- Do not download large supplementary files without checking disk space and file purpose.
- Do not treat probe identifiers as gene symbols without platform-specific annotation mapping.
Frequently Asked Questions
What is NCBI GEO?
Can this skill download GEO files?
Does it support RNA-seq and microarray data?
Does it perform final statistical interpretation?
What tools does it expect?
How should I handle API keys?
Developer Details
Author
K-Dense-AILicense
Unknown
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/geo-databaseRef
26421118b848d9f1efc0aa169d8a7a9e7e0a877e
Maintenance freshness
7/18/2026
Usage
8 downloads ยท 220 views
File structure