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.