Retrieve GEO gene expression datasets and metadata via Entrez and GEOparse workflows.
npx skills add https://github.com/jackspace/ClaudeSkillz --skill geo-database
Please help me install this Agent Skill. Skill: geo-database Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/geo-database Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill geo-database
This Skill provides practical approaches to access and retrieve GEO data (GSE, GSM, GPL) for transcriptomics and expression analysis using GEOparse and E-utilities.
Use GEOparse to fetch a GSE, extract its expression matrix, and inspect sample metadata.
High-intent search queries and answers about installing and using this skill.
Use GEOparse to programmatically fetch GSE (Series) records from NCBI GEO, which automatically retrieves expression matrices and sample metadata. GEOparse handles SOFT file parsing and provides direct access to raw and processed expression data for transcriptomics workflows.
GEO organizes data hierarchically: GSE (Series) contains multiple GSM (Samples) from a single study, GPL (Platform) describes the microarray or sequencing technology used, and GDS (DataSet) provides curated, comparable datasets. Understanding this hierarchy is essential for retrieving the correct data level for your analysis.
Yes. GEOparse loads GSE records and directly exposes both the expression matrix and sample metadata (phenotypes, annotations). You can programmatically access SOFT/Matrix files and supplementary data without manual downloads, streamlining data preparation for downstream analysis.
Use NCBI E-utilities (Entrez) to search GEO DataSets and Profiles, retrieve metadata, and construct queries for Series and Samples. GEOparse integrates with Entrez to automate GEO lookups and downloads, replacing manual web searches with reproducible Python scripts.
Familiarity with gene expression concepts, microarray or RNA-seq protocols, and Python is helpful. GEOparse abstracts file format complexity, but understanding GEO's hierarchical structure and SOFT file organization ensures efficient data retrieval and correct interpretation of expression profiles.
Yes. GEOparse retrieves supplementary files associated with GSE records, enabling access to raw sequencing data, processed counts, and additional experimental files. This supports complete data retrieval workflows without switching between tools or manual downloads.
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