If you're working with single-cell genomics data, this is the data structure you'll be using whether you realize it or not. It's the foundation under scanpy, scvi-tools, and most of the scverse ecosystem. Think of it as a specialized container that bundles your expression matrix with all the metadata about cells and genes, plus support for sparse matrices and lazy loading when files get huge. The skill covers creating and manipulating these objects, reading h5ad and zarr files, concatenating datasets from multiple batches, and staying memory-efficient with backed mode. One thing to note is that for actual 10X file reading you'll want the scanpy skill instead, since those convenience functions live there now.
- skills.sh installs
- 2.1K
- GitHub stars
- 56.6K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill anndata --agent claude-codeInstalls into .claude/skills of the current project.
Files
AnnData
Overview
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs), variable metadata (var), and multi-dimensional annotations (obsm, varm, obsp, varp, uns). Originally designed for single-cell genomics through Scanpy, it now serves as a general-purpose framework for any annotated data requiring efficient storage, manipulation, and analysis.
When to Use This Skill
Use this skill when:
- Creating, reading, or writing AnnData objects
- Working with h5ad, zarr, or other genomics data formats
- Performing single-cell RNA-seq analysis
- Managing large datasets with sparse matrices or backed mode
- Concatenating multiple datasets or experimental batches
- Subsetting, filtering, or transforming annotated data
- Integrating with scanpy, scvi-tools, or other scverse ecosystem tools
Installation
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- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- Code Review & Quality, AI & Agent Building
- First seen
- Jun 3, 2026
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