anndata

# 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 ```bash uv pip install anndata # With optional dependencies uv pip install anndata[dev,test,doc] ``` ## Quick Start ### Creating an AnnData object ```python import anndata as ad import numpy as np import pandas as pd # Minimal creation X = np.random.rand(100, 2000) # 100 cells × 2000 genes adata = ad.AnnData(X) # With metadata obs = pd.DataFrame({ 'cell_type': ['T cell', 'B cell'] * 50, 'sample': ['A', 'B'] * 50 }, index=[f'cell_{i}' for i in range(100)]) var = pd.DataFrame({ 'gene_name': [f'Gene_{i}' for i in range(2000)] }, index=[f'ENSG{i:05d}' for i in range(2000)])...