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datasets-loading

Load OmicVerse built-in datasets and generate mock data for testing.

32|5|Updated Mar 12, 2026
Search Tags:#cache#download#single-cell#signatures#mock-data#datasets#scrna-seq
One-click install
npx skills add https://github.com/omicverse/omicclaw --skill datasets-loading-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datasets-loading
Source: https://github.com/omicverse/omicclaw/tree/main/src/omicverse_skills/skills/datasets-loading
Command: npx skills add https://github.com/omicverse/omicclaw --skill datasets-loading-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OmicVerse built-in datasets provide ready-to-use datasets (pbmc3k, pancreas, dentategyrus, zebrafish, immune, spatial, multiome) and a helper create_mock_dataset() to generate synthetic data, reducing the need for network downloads in demos and tests.

Core Features & Use Cases

  • Built-in dataset catalog with automatic download, caching, and fallback to mock data.
  • Mock data generation via create_mock_dataset() for testing without network access.
  • Predefined GMT gene signatures via predefined_signatures for common analyses.
  • Use cases include Quick demos, unit tests, and benchmarking pipelines.

Quick Start

Load a built-in dataset with ov.datasets.pbmc3k() and generate a mock dataset with ov.datasets.create_mock_dataset().

Frequently Asked Questions about datasets-loading

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I load single-cell datasets for quick demos without downloading from the network?▼

You can load single-cell datasets directly using built-in functions like ov.datasets.pbmc3k(), which automatically handles downloading, internal caching, and fallback to mock data for reproducible demos.

Can I generate synthetic scRNA-seq data for unit tests when I have no network access?▼

Yes, you can generate synthetic scRNA-seq data without network access by using the create_mock_dataset() helper, which creates mock data specifically designed for testing and fast prototyping.

What built-in datasets are available for single-cell analysis workflows?▼

Available built-in datasets include pbmc3k, pancreas, dentategyrus, zebrafish, immune, spatial, and multiome, providing ready-to-use data for tutorials, benchmarks, and analysis workflows.

Does this approach provide predefined gene signatures for common single-cell analyses?▼

Yes, predefined GMT gene signatures are available via predefined_signatures, supplying common gene sets needed to run gene signature analysis on single-cell datasets.

What is the best way to ensure reproducible results when prototyping single-cell pipelines?▼

The best way to ensure reproducible results is to use built-in datasets with internal caching and mock data generation, which reduces network dependency and provides consistent data for benchmarking pipelines.

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