What problem does it solve?
AnnData provides a standard, efficient container for annotated experimental matrices so you can store measurements together with observation and feature metadata and reliably move data through single-cell workflows.
Core Features & Use Cases
- Unified annotated data model: Represents the main matrix X plus obs (observations), var (variables/features), and additional fields like layers, embeddings (obsm), pairwise graphs (obsp), and unstructured metadata (uns).
- Fast I/O for research datasets: Load and save common genomics formats (especially .h5ad and zarr) and convert between them for downstream tools.
- Practical single-cell operations: Subset, filter, concatenate across batches/modalities, transpose axes when needed, and follow memory-friendly practices for large or sparse data.
- Ecosystem interoperability: Acts as the foundational object for scverse tools such as Scanpy, and supports integrations for multimodal data and model training workflows.
Quick Start
Use the anndata skill to load a single-cell dataset from an .h5ad file named data.h5ad into an AnnData object for further analysis.