What this resource does

Core uses

About this resource

bioSkills is a collection of 562 Skill files that guide supported coding agents through bioinformatics tasks including sequence work, variant analysis, single-cell data, genomics, proteomics, statistics, and visualisation.

This page groups representative academic components by task; review the repository for the complete inventory.

I want toGenomic variant and causal analysis I want toSingle-cell and transcriptomic analysis I want toBioinformatics visualisation and reporting

Genomic variant and causal analysis

Includes Skills for variant annotation, prioritisation, fine mapping, association, Mendelian randomisation, and related genomic methods.

Typical inputs: Compatible variant or summary-statistic data; Reference build, phenotype definitions, and method assumptions
Output: Component-dependent code, tables, figures, or variant-analysis reports.

Best for: Research projects with defined genomic inputs and a reviewed analysis plan.

Skills for this task

variant-prioritization

Guides a clinical-database variant-prioritisation workflow.

Official guide

fine-mapping

Guides a causal-genomics fine-mapping analysis.

Official guide

Single-cell and transcriptomic analysis

Provides Skills for single-cell data input, quality control, clustering, annotation, integration, and RNA analysis.

Typical inputs: Expression matrix, cell metadata, and analysis objective
Output: Component-dependent analysis code, processed objects, tables, and figures.

Best for: Planning or implementing a defined single-cell or transcriptomics workflow.

Skills for this task

single-cell-clustering

Supports clustering within a single-cell workflow.

Official guide

single-cell-annotation

Supports cell-type annotation in single-cell data.

Official guide

Bioinformatics visualisation and reporting

Contains Skills for genome tracks, enrichment plots, phylogenetic trees, protein maps, and other research visualisations.

Typical inputs: Processed data, plot objective, labels, and output requirements
Output: Visualisation code and a component-dependent scientific figure.

Best for: Turning checked bioinformatics results into an interpretable figure.

Skills for this task

genome-tracks

Creates genome-track visualisations from compatible data.

Official guide

enrichment-visualization

Creates pathway or enrichment visualisations.

Official guide

Use boundaries

Limits and checks

Large dependency surface

Installing everything can create conflicts or an unnecessarily broad environment.

Use the category or project installer and isolate the environment.

Biological versioning

Code may run while producing results that are not comparable with the intended study.

Record and check all data, reference, and tool versions.

Sensitive biological data

Agent tools or external resources may expose sensitive data.

Use approved environments and inspect each Skill for network or API use.

More boundaries

Do not install or invoke the whole collection when the project only needs a small set of bioinformatics categories.
A Skill cannot run an analysis without compatible data, reference versions, packages, command-line tools, and enough compute.
Generated code and figures do not establish that a statistical or biological interpretation is valid.

Technical details

Resource type: Skill Collection
Author or maintainer: GPTomics
Latest release: 3.0
Source last updated: 15 Jul 2026
Last verified: 15 Jul 2026
Documented applications: Claude Code, Codex, OpenClaw, Antigravity CLI, OpenCode
Licence: MIT
Access: Publicly available
Additional costs: Platform terms or usage limits may apply. API usage fees may apply for selected components. External services, software, compute, or data access may have separate costs.
Skill instruction language: English
Documentation language: English
Repository languages: Python, Markdown
Dependencies: Supported coding agent; Git and shell; Skill-specific Python, R, Bioconductor, command-line tools, and reference data
Review status: Not tested

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