anndata

Load, save, subset, concatenate, and restructure AnnData objects across h5ad and zarr formats.

Updated Jul 1, 2026
One-click install
npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill anndata-jasrajtulsi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: anndata
Source: https://github.com/jasrajtulsi/GRAD-SCOPE/tree/main/.claude/skills/anndata
Command: npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill anndata-jasrajtulsi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill removes the friction of working with annotated matrices in single-cell and other high-dimensional analysis workflows. It helps you read, write, structure, subset, and combine AnnData objects while keeping observations, variables, layers, embeddings, and metadata aligned.

Core Features & Use Cases

  • Data structure management: Create and inspect AnnData objects with X, obs, var, layers, obsm, varm, obsp, varp, uns, and raw.
  • I/O and interoperability: Load and save h5ad, zarr, csv, mtx, loom, Excel, and other supported formats for robust data exchange.
  • Concatenation and manipulation: Merge batches, reorder or filter cells and genes, and preserve metadata integrity during subsetting or transformation.
  • Best-practice workflows: Use backed mode, sparse matrices, categoricals, and chunked processing to handle large datasets efficiently.
  • Use case: A researcher can load multiple single-cell batches, merge them into one AnnData object, filter low-quality cells, and save the processed result for Scanpy or scverse tools.

Quick Start

Use the anndata skill to help me load a .h5ad file, inspect its metadata, and suggest the safest way to subset and save it for downstream single-cell analysis.

Frequently Asked Questions about anndata

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

FAQPage Schema
How do I load and inspect a single-cell h5ad file for downstream analysis?▼

To load and inspect a single-cell h5ad file, read the AnnData object into memory and access its X matrix alongside obs and var metadata. This ensures observations and variables remain aligned for immediate scverse or Scanpy workflows.

What is the best way to concatenate multiple single-cell batches into one AnnData object?▼

Concatenating multiple single-cell batches involves merging AnnData objects while preserving observations, variables, and layers. You can combine batches and maintain metadata integrity across obs and var to ensure seamless downstream analysis.

Can I use backed mode and sparse matrices for memory-efficient AnnData processing?▼

Yes, backed mode and sparse matrices enable memory-efficient AnnData processing for large datasets. These best-practice workflows allow chunked processing and categorical handling without loading entire high-dimensional matrices into memory.

Does AnnData support saving and loading zarr formats for high-dimensional data?▼

AnnData supports saving and loading zarr formats alongside h5ad, csv, mtx, and loom for robust data exchange. This I/O interoperability allows you to structure and save annotated matrices for scverse-compatible preparation.

How do I subset and filter cells or genes while preserving AnnData metadata alignment?▼

Subsetting and filtering cells or genes preserves AnnData metadata alignment by automatically adjusting obs, var, layers, and embeddings simultaneously. This restructuring maintains metadata integrity during transformations without manual index correction.